librarian-bots/model_cards_with_metadata · Datasets at Hugging Face

modelId stringlengths 5 139	author stringlengths 2 42	last_modified timestamp[us, tz=UTC]date 2020-02-15 11:33:14 2025-06-25 18:28:32	downloads int64 0 223M	likes int64 0 11.7k	library_name stringclasses 495 values	tags sequencelengths 1 4.05k	pipeline_tag stringclasses 54 values	createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2025-06-25 18:28:16	card stringlengths 11 1.01M
Vellimani/Mistral-7B-Instruct-v0.2-finetuned-QA	Vellimani	2024-06-05T05:43:37Z	8	0	transformers	[ "transformers", "safetensors", "mistral", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-04T08:15:43Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
tyzhu/squad_qa_title_v5_full_recite_full_passage_meta-llama_Llama-2-7b-hf_1e-4_lora	tyzhu	2024-06-05T05:40:11Z	0	0	null	[ "generated_from_trainer", "base_model:meta-llama/Llama-2-7b-hf", "base_model:finetune:meta-llama/Llama-2-7b-hf", "license:llama2", "region:us" ]	null	2024-06-05T01:47:22Z	--- license: llama2 base_model: meta-llama/Llama-2-7b-hf tags: - generated_from_trainer metrics: - accuracy model-index: - name: squad_qa_title_v5_full_recite_full_passage_meta-llama_Llama-2-7b-hf_1e-4_lora results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # squad_qa_title_v5_full_recite_full_passage_meta-llama_Llama-2-7b-hf_1e-4_lora This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3478 - Accuracy: 0.8669 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 1 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - total_eval_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 50.0 ### Training results \| Training Loss \| Epoch \| Step \| Accuracy \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:--------:\|:---------------:\| \| 1.2097 \| 1.0 \| 158 \| 0.8026 \| 0.6959 \| \| 0.2421 \| 2.0 \| 317 \| 0.8546 \| 0.2840 \| \| 0.1304 \| 3.0 \| 475 \| 0.8658 \| 0.2053 \| \| 0.1007 \| 4.0 \| 634 \| 0.8667 \| 0.2005 \| \| 0.0941 \| 5.0 \| 792 \| 0.8665 \| 0.2082 \| \| 0.0838 \| 6.0 \| 951 \| 0.8669 \| 0.2144 \| \| 0.0745 \| 7.0 \| 1109 \| 0.8673 \| 0.2232 \| \| 0.0667 \| 8.0 \| 1268 \| 0.8667 \| 0.2343 \| \| 0.0602 \| 9.0 \| 1426 \| 0.8664 \| 0.2490 \| \| 0.0558 \| 10.0 \| 1585 \| 0.8659 \| 0.2618 \| \| 0.0519 \| 11.0 \| 1743 \| 0.8674 \| 0.2661 \| \| 0.05 \| 12.0 \| 1902 \| 0.8680 \| 0.2679 \| \| 0.0475 \| 13.0 \| 2060 \| 0.8664 \| 0.2857 \| \| 0.0484 \| 14.0 \| 2219 \| 0.8660 \| 0.2898 \| \| 0.0466 \| 15.0 \| 2377 \| 0.8664 \| 0.2856 \| \| 0.0464 \| 16.0 \| 2536 \| 0.8661 \| 0.3037 \| \| 0.045 \| 17.0 \| 2694 \| 0.8660 \| 0.2976 \| \| 0.0459 \| 18.0 \| 2853 \| 0.8660 \| 0.2930 \| \| 0.0478 \| 19.0 \| 3011 \| 0.8664 \| 0.2994 \| \| 0.0444 \| 20.0 \| 3170 \| 0.8665 \| 0.3027 \| \| 0.0443 \| 21.0 \| 3328 \| 0.8662 \| 0.2945 \| \| 0.0432 \| 22.0 \| 3487 \| 0.8665 \| 0.3020 \| \| 0.0427 \| 23.0 \| 3645 \| 0.8664 \| 0.3122 \| \| 0.0436 \| 24.0 \| 3804 \| 0.8663 \| 0.3181 \| \| 0.0424 \| 25.0 \| 3962 \| 0.8661 \| 0.3300 \| \| 0.0442 \| 26.0 \| 4121 \| 0.8662 \| 0.3173 \| \| 0.0455 \| 27.0 \| 4279 \| 0.8659 \| 0.2914 \| \| 0.0464 \| 28.0 \| 4438 \| 0.8663 \| 0.3043 \| \| 0.0446 \| 29.0 \| 4596 \| 0.8664 \| 0.3201 \| \| 0.0427 \| 30.0 \| 4755 \| 0.8666 \| 0.3103 \| \| 0.0428 \| 31.0 \| 4913 \| 0.8668 \| 0.3120 \| \| 0.0422 \| 32.0 \| 5072 \| 0.8665 \| 0.3209 \| \| 0.0422 \| 33.0 \| 5230 \| 0.8664 \| 0.3256 \| \| 0.0426 \| 34.0 \| 5389 \| 0.8665 \| 0.3295 \| \| 0.0423 \| 35.0 \| 5547 \| 0.8667 \| 0.3375 \| \| 0.0421 \| 36.0 \| 5706 \| 0.8666 \| 0.3299 \| \| 0.0416 \| 37.0 \| 5864 \| 0.8664 \| 0.3438 \| \| 0.0429 \| 38.0 \| 6023 \| 0.8657 \| 0.3313 \| \| 0.0455 \| 39.0 \| 6181 \| 0.8661 \| 0.3100 \| \| 0.0433 \| 40.0 \| 6340 \| 0.8663 \| 0.3111 \| \| 0.0435 \| 41.0 \| 6498 \| 0.8666 \| 0.3134 \| \| 0.042 \| 42.0 \| 6657 \| 0.8667 \| 0.3188 \| \| 0.042 \| 43.0 \| 6815 \| 0.8668 \| 0.3219 \| \| 0.0413 \| 44.0 \| 6974 \| 0.8666 \| 0.3348 \| \| 0.0416 \| 45.0 \| 7110 \| 0.3498 \| 0.8666 \| \| 0.0413 \| 46.0 \| 7269 \| 0.3380 \| 0.8666 \| \| 0.0418 \| 47.0 \| 7427 \| 0.3580 \| 0.8668 \| \| 0.041 \| 48.0 \| 7586 \| 0.3516 \| 0.8667 \| \| 0.0411 \| 49.0 \| 7744 \| 0.3468 \| 0.8669 \| \| 0.0417 \| 49.98 \| 7900 \| 0.3478 \| 0.8669 \| ### Framework versions - Transformers 4.34.0 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.14.1
LarryAIDraw/taoqi	LarryAIDraw	2024-06-05T05:35:09Z	0	0	null	[ "license:creativeml-openrail-m", "region:us" ]	null	2024-06-05T05:30:29Z	--- license: creativeml-openrail-m --- https://civitai.com/models/495578/taoqi-or-wuthering-waves
LarryAIDraw/genshin_v4	LarryAIDraw	2024-06-05T05:34:59Z	0	0	null	[ "license:creativeml-openrail-m", "region:us" ]	null	2024-06-05T05:30:04Z	--- license: creativeml-openrail-m --- https://civitai.com/models/357976/ponyall-characters-genshin-impact-124-characters-124
llama-duo/gemma2b-summarize-claude3sonnet-16k	llama-duo	2024-06-05T05:31:32Z	2	0	peft	[ "peft", "tensorboard", "safetensors", "gemma", "alignment-handbook", "trl", "sft", "generated_from_trainer", "dataset:llama-duo/synth_summarize_dataset_dedup", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "license:gemma", "4-bit", "bitsandbytes", "region:us" ]	null	2024-06-05T05:02:09Z	--- license: gemma library_name: peft tags: - alignment-handbook - trl - sft - generated_from_trainer base_model: google/gemma-2b datasets: - llama-duo/synth_summarize_dataset_dedup model-index: - name: gemma2b-summarize-claude3sonnet-16k results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # gemma2b-summarize-claude3sonnet-16k This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.5454 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 3 - gradient_accumulation_steps: 2 - total_train_batch_size: 48 - total_eval_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:---------------:\| \| 1.4889 \| 1.0 \| 51 \| 2.5875 \| \| 1.1695 \| 2.0 \| 102 \| 2.5044 \| \| 1.1003 \| 3.0 \| 153 \| 2.5000 \| \| 1.0537 \| 4.0 \| 204 \| 2.5040 \| \| 1.0131 \| 5.0 \| 255 \| 2.5131 \| \| 0.995 \| 6.0 \| 306 \| 2.5208 \| \| 0.9739 \| 7.0 \| 357 \| 2.5337 \| \| 0.9626 \| 8.0 \| 408 \| 2.5445 \| \| 0.9572 \| 9.0 \| 459 \| 2.5443 \| \| 0.9554 \| 10.0 \| 510 \| 2.5454 \| ### Framework versions - PEFT 0.10.0 - Transformers 4.40.0 - Pytorch 2.2.2+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1
zyylol/ppo-LunarLander-v2	zyylol	2024-06-05T05:30:09Z	0	0	stable-baselines3	[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]	reinforcement-learning	2024-06-04T07:10:57Z	--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 272.60 +/- 16.14 name: mean_reward verified: false --- # PPO Agent playing LunarLander-v2 This is a trained model of a PPO agent playing LunarLander-v2 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
imlixinyang/director3d	imlixinyang	2024-06-05T05:29:44Z	0	0	null	[ "license:cc-by-nc-nd-4.0", "region:us" ]	null	2024-06-05T05:12:18Z	--- license: cc-by-nc-nd-4.0 ---
tsavage68/UTI_L3_1000steps_1e6rate_05beta_CSFTDPO	tsavage68	2024-06-05T05:28:47Z	6	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T05:24:46Z	--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e6rate_05beta_CSFTDPO results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # UTI_L3_1000steps_1e6rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0078 - Rewards/chosen: 2.5926 - Rewards/rejected: -13.7164 - Rewards/accuracies: 0.9900 - Rewards/margins: 16.3089 - Logps/rejected: -90.6274 - Logps/chosen: -27.2939 - Logits/rejected: -1.3641 - Logits/chosen: -1.3371 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-06 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rewards/chosen \| Rewards/rejected \| Rewards/accuracies \| Rewards/margins \| Logps/rejected \| Logps/chosen \| Logits/rejected \| Logits/chosen \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:--------------:\|:----------------:\|:------------------:\|:---------------:\|:--------------:\|:------------:\|:---------------:\|:-------------:\| \| 0.5483 \| 0.3333 \| 25 \| 0.2812 \| 0.2629 \| -1.0915 \| 0.9900 \| 1.3544 \| -65.3776 \| -31.9532 \| -1.3242 \| -1.3091 \| \| 0.0186 \| 0.6667 \| 50 \| 0.0204 \| 1.4814 \| -6.2620 \| 0.9900 \| 7.7434 \| -75.7187 \| -29.5163 \| -1.3323 \| -1.3150 \| \| 0.0007 \| 1.0 \| 75 \| 0.0124 \| 2.1023 \| -8.8403 \| 0.9900 \| 10.9426 \| -80.8753 \| -28.2744 \| -1.3425 \| -1.3227 \| \| 0.0174 \| 1.3333 \| 100 \| 0.0110 \| 2.7866 \| -9.0480 \| 0.9900 \| 11.8346 \| -81.2906 \| -26.9057 \| -1.3476 \| -1.3272 \| \| 0.0173 \| 1.6667 \| 125 \| 0.0107 \| 2.2710 \| -10.8326 \| 0.9900 \| 13.1036 \| -84.8600 \| -27.9370 \| -1.3498 \| -1.3269 \| \| 0.0348 \| 2.0 \| 150 \| 0.0079 \| 2.5738 \| -13.4526 \| 0.9900 \| 16.0264 \| -90.0999 \| -27.3315 \| -1.3620 \| -1.3349 \| \| 0.0 \| 2.3333 \| 175 \| 0.0079 \| 2.5665 \| -13.4456 \| 0.9900 \| 16.0121 \| -90.0858 \| -27.3459 \| -1.3620 \| -1.3348 \| \| 0.0 \| 2.6667 \| 200 \| 0.0078 \| 2.5714 \| -13.4484 \| 0.9900 \| 16.0198 \| -90.0914 \| -27.3362 \| -1.3619 \| -1.3348 \| \| 0.0 \| 3.0 \| 225 \| 0.0079 \| 2.5744 \| -13.4805 \| 0.9900 \| 16.0549 \| -90.1557 \| -27.3302 \| -1.3623 \| -1.3352 \| \| 0.0173 \| 3.3333 \| 250 \| 0.0078 \| 2.5790 \| -13.4989 \| 0.9900 \| 16.0779 \| -90.1926 \| -27.3210 \| -1.3623 \| -1.3352 \| \| 0.0173 \| 3.6667 \| 275 \| 0.0077 \| 2.5749 \| -13.5072 \| 0.9900 \| 16.0821 \| -90.2091 \| -27.3291 \| -1.3623 \| -1.3351 \| \| 0.0347 \| 4.0 \| 300 \| 0.0078 \| 2.5828 \| -13.5202 \| 0.9900 \| 16.1030 \| -90.2351 \| -27.3134 \| -1.3626 \| -1.3355 \| \| 0.0 \| 4.3333 \| 325 \| 0.0077 \| 2.5858 \| -13.5544 \| 0.9900 \| 16.1403 \| -90.3036 \| -27.3074 \| -1.3626 \| -1.3355 \| \| 0.0173 \| 4.6667 \| 350 \| 0.0078 \| 2.5816 \| -13.5650 \| 0.9900 \| 16.1466 \| -90.3246 \| -27.3158 \| -1.3628 \| -1.3357 \| \| 0.0347 \| 5.0 \| 375 \| 0.0079 \| 2.5779 \| -13.5622 \| 0.9900 \| 16.1400 \| -90.3190 \| -27.3233 \| -1.3628 \| -1.3356 \| \| 0.0173 \| 5.3333 \| 400 \| 0.0077 \| 2.5852 \| -13.5789 \| 0.9900 \| 16.1641 \| -90.3526 \| -27.3087 \| -1.3630 \| -1.3358 \| \| 0.0347 \| 5.6667 \| 425 \| 0.0078 \| 2.5848 \| -13.6053 \| 0.9900 \| 16.1901 \| -90.4053 \| -27.3094 \| -1.3632 \| -1.3361 \| \| 0.0173 \| 6.0 \| 450 \| 0.0077 \| 2.5855 \| -13.6105 \| 0.9900 \| 16.1960 \| -90.4156 \| -27.3079 \| -1.3634 \| -1.3364 \| \| 0.0 \| 6.3333 \| 475 \| 0.0079 \| 2.5850 \| -13.6238 \| 0.9900 \| 16.2087 \| -90.4422 \| -27.3091 \| -1.3635 \| -1.3364 \| \| 0.0347 \| 6.6667 \| 500 \| 0.0077 \| 2.5926 \| -13.6436 \| 0.9900 \| 16.2362 \| -90.4819 \| -27.2938 \| -1.3635 \| -1.3364 \| \| 0.0 \| 7.0 \| 525 \| 0.0077 \| 2.5890 \| -13.6520 \| 0.9900 \| 16.2410 \| -90.4987 \| -27.3010 \| -1.3635 \| -1.3364 \| \| 0.0 \| 7.3333 \| 550 \| 0.0077 \| 2.5868 \| -13.6463 \| 0.9900 \| 16.2331 \| -90.4873 \| -27.3054 \| -1.3636 \| -1.3365 \| \| 0.0173 \| 7.6667 \| 575 \| 0.0077 \| 2.5918 \| -13.6721 \| 0.9900 \| 16.2639 \| -90.5389 \| -27.2955 \| -1.3637 \| -1.3366 \| \| 0.0347 \| 8.0 \| 600 \| 0.0078 \| 2.5868 \| -13.6787 \| 0.9900 \| 16.2654 \| -90.5520 \| -27.3055 \| -1.3638 \| -1.3367 \| \| 0.0347 \| 8.3333 \| 625 \| 0.0077 \| 2.5930 \| -13.6789 \| 0.9900 \| 16.2719 \| -90.5525 \| -27.2931 \| -1.3639 \| -1.3368 \| \| 0.0 \| 8.6667 \| 650 \| 0.0078 \| 2.5892 \| -13.6871 \| 0.9900 \| 16.2763 \| -90.5689 \| -27.3006 \| -1.3638 \| -1.3367 \| \| 0.0 \| 9.0 \| 675 \| 0.0077 \| 2.5903 \| -13.6943 \| 0.9900 \| 16.2847 \| -90.5834 \| -27.2984 \| -1.3639 \| -1.3368 \| \| 0.0173 \| 9.3333 \| 700 \| 0.0078 \| 2.5860 \| -13.7028 \| 0.9900 \| 16.2888 \| -90.6002 \| -27.3070 \| -1.3642 \| -1.3371 \| \| 0.0173 \| 9.6667 \| 725 \| 0.0077 \| 2.5865 \| -13.6964 \| 0.9900 \| 16.2830 \| -90.5876 \| -27.3060 \| -1.3641 \| -1.3370 \| \| 0.0 \| 10.0 \| 750 \| 0.0077 \| 2.5939 \| -13.7066 \| 0.9900 \| 16.3006 \| -90.6079 \| -27.2912 \| -1.3641 \| -1.3370 \| \| 0.0 \| 10.3333 \| 775 \| 0.0079 \| 2.5928 \| -13.7020 \| 0.9900 \| 16.2947 \| -90.5986 \| -27.2935 \| -1.3640 \| -1.3369 \| \| 0.0173 \| 10.6667 \| 800 \| 0.0078 \| 2.5909 \| -13.7013 \| 0.9900 \| 16.2922 \| -90.5973 \| -27.2972 \| -1.3642 \| -1.3371 \| \| 0.0173 \| 11.0 \| 825 \| 0.0076 \| 2.5913 \| -13.7123 \| 0.9900 \| 16.3036 \| -90.6193 \| -27.2965 \| -1.3641 \| -1.3370 \| \| 0.0 \| 11.3333 \| 850 \| 0.0077 \| 2.5908 \| -13.7072 \| 0.9900 \| 16.2980 \| -90.6090 \| -27.2974 \| -1.3642 \| -1.3371 \| \| 0.0347 \| 11.6667 \| 875 \| 0.0078 \| 2.5953 \| -13.7055 \| 0.9900 \| 16.3008 \| -90.6056 \| -27.2884 \| -1.3640 \| -1.3369 \| \| 0.0 \| 12.0 \| 900 \| 0.0078 \| 2.5866 \| -13.7139 \| 0.9900 \| 16.3005 \| -90.6224 \| -27.3058 \| -1.3642 \| -1.3370 \| \| 0.0173 \| 12.3333 \| 925 \| 0.0077 \| 2.5953 \| -13.6932 \| 0.9900 \| 16.2885 \| -90.5811 \| -27.2884 \| -1.3640 \| -1.3369 \| \| 0.0173 \| 12.6667 \| 950 \| 0.0077 \| 2.5928 \| -13.7129 \| 0.9900 \| 16.3057 \| -90.6204 \| -27.2934 \| -1.3641 \| -1.3370 \| \| 0.0347 \| 13.0 \| 975 \| 0.0078 \| 2.5926 \| -13.7164 \| 0.9900 \| 16.3089 \| -90.6274 \| -27.2939 \| -1.3641 \| -1.3371 \| \| 0.0 \| 13.3333 \| 1000 \| 0.0078 \| 2.5926 \| -13.7164 \| 0.9900 \| 16.3089 \| -90.6274 \| -27.2939 \| -1.3641 \| -1.3371 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1
nuttcutee/Custom_tiger_google_vit-base-patch16-224	nuttcutee	2024-06-05T05:14:10Z	219	0	transformers	[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-06-05T05:13:51Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
llama-duo/gemma2b-summarize-gemini1_5flash-16k	llama-duo	2024-06-05T05:05:24Z	2	0	peft	[ "peft", "tensorboard", "safetensors", "gemma", "alignment-handbook", "trl", "sft", "generated_from_trainer", "dataset:llama-duo/synth_summarize_dataset_dedup", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "license:gemma", "4-bit", "bitsandbytes", "region:us" ]	null	2024-06-05T04:50:07Z	--- license: gemma library_name: peft tags: - alignment-handbook - trl - sft - generated_from_trainer base_model: google/gemma-2b datasets: - llama-duo/synth_summarize_dataset_dedup model-index: - name: gemma2b-summarize-gemini1_5flash-16k results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # gemma2b-summarize-gemini1_5flash-16k This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.5319 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 2.0246 \| 0.9811 \| 26 \| 2.6613 \| \| 1.3202 \| 2.0 \| 53 \| 2.5405 \| \| 1.1694 \| 2.9811 \| 79 \| 2.5125 \| \| 1.1076 \| 4.0 \| 106 \| 2.5138 \| \| 1.0651 \| 4.9811 \| 132 \| 2.5086 \| \| 1.0394 \| 6.0 \| 159 \| 2.5248 \| \| 1.0232 \| 6.9811 \| 185 \| 2.5264 \| \| 1.0042 \| 8.0 \| 212 \| 2.5296 \| \| 1.0109 \| 8.9811 \| 238 \| 2.5319 \| \| 1.0064 \| 9.8113 \| 260 \| 2.5319 \| ### Framework versions - PEFT 0.11.1 - Transformers 4.40.1 - Pytorch 2.2.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1
msubhasish28/my_awesome_model	msubhasish28	2024-06-05T04:49:49Z	105	0	transformers	[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-15T01:32:32Z	--- license: apache-2.0 base_model: distilbert/distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: my_awesome_model results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # my_awesome_model This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2265 - Accuracy: 0.9326 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| 0.2257 \| 1.0 \| 1563 \| 0.1940 \| 0.9259 \| \| 0.1446 \| 2.0 \| 3126 \| 0.2265 \| 0.9326 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.2.2 - Datasets 2.14.6 - Tokenizers 0.19.1
alpcansoydas/iban_ocr_large_18k_epoch5	alpcansoydas	2024-06-05T04:49:22Z	50	0	transformers	[ "transformers", "safetensors", "vision-encoder-decoder", "image-text-to-text", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	image-text-to-text	2024-06-05T01:14:43Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> [{'loss': 3.0878, 'learning_rate': 4.8630820399113085e-05, 'epoch': 0.14, 'step': 500}, {'loss': 1.9885, 'learning_rate': 4.7245011086474504e-05, 'epoch': 0.28, 'step': 1000}, {'loss': 1.7381, 'learning_rate': 4.585920177383592e-05, 'epoch': 0.42, 'step': 1500}, {'loss': 1.4517, 'learning_rate': 4.447339246119734e-05, 'epoch': 0.55, 'step': 2000}, {'loss': 1.225, 'learning_rate': 4.3087583148558755e-05, 'epoch': 0.69, 'step': 2500}, {'loss': 1.1094, 'learning_rate': 4.1704545454545456e-05, 'epoch': 0.83, 'step': 3000}, {'loss': 1.0243, 'learning_rate': 4.0318736141906875e-05, 'epoch': 0.97, 'step': 3500}, {'eval_loss': 0.9151868224143982, 'eval_cer': 0.1013281301966697, 'eval_runtime': 2841.3659, 'eval_samples_per_second': 1.27, 'eval_steps_per_second': 0.317, 'epoch': 1.0, 'step': 3608}, {'loss': 0.8896, 'learning_rate': 3.8932926829268294e-05, 'epoch': 1.11, 'step': 4000}, {'loss': 0.7499, 'learning_rate': 3.754711751662971e-05, 'epoch': 1.25, 'step': 4500}, {'loss': 0.7259, 'learning_rate': 3.616130820399113e-05, 'epoch': 1.39, 'step': 5000}, {'loss': 0.7324, 'learning_rate': 3.477549889135255e-05, 'epoch': 1.52, 'step': 5500}, {'loss': 0.6456, 'learning_rate': 3.338968957871397e-05, 'epoch': 1.66, 'step': 6000}, {'loss': 0.563, 'learning_rate': 3.200388026607539e-05, 'epoch': 1.8, 'step': 6500}, {'loss': 0.5532, 'learning_rate': 3.061807095343681e-05, 'epoch': 1.94, 'step': 7000}, {'eval_loss': 0.43645456433296204, 'eval_cer': 0.037061262499722844, 'eval_runtime': 2791.7981, 'eval_samples_per_second': 1.292, 'eval_steps_per_second': 0.323, 'epoch': 2.0, 'step': 7216}, {'loss': 0.4441, 'learning_rate': 2.9235033259423506e-05, 'epoch': 2.08, 'step': 7500}, {'loss': 0.4233, 'learning_rate': 2.7849223946784925e-05, 'epoch': 2.22, 'step': 8000}, {'loss': 0.3911, 'learning_rate': 2.646618625277162e-05, 'epoch': 2.36, 'step': 8500}, {'loss': 0.3454, 'learning_rate': 2.5080376940133038e-05, 'epoch': 2.49, 'step': 9000}, {'loss': 0.3201, 'learning_rate': 2.3694567627494457e-05, 'epoch': 2.63, 'step': 9500}, {'loss': 0.2908, 'learning_rate': 2.2308758314855876e-05, 'epoch': 2.77, 'step': 10000}, {'loss': 0.2651, 'learning_rate': 2.0922949002217295e-05, 'epoch': 2.91, 'step': 10500}, {'eval_loss': 0.26305779814720154, 'eval_cer': 0.021252300392452496, 'eval_runtime': 2821.9411, 'eval_samples_per_second': 1.279, 'eval_steps_per_second': 0.32, 'epoch': 3.0, 'step': 10824}, {'loss': 0.2313, 'learning_rate': 1.9537139689578714e-05, 'epoch': 3.05, 'step': 11000}, {'loss': 0.1767, 'learning_rate': 1.8151330376940133e-05, 'epoch': 3.19, 'step': 11500}, {'loss': 0.196, 'learning_rate': 1.6765521064301552e-05, 'epoch': 3.33, 'step': 12000}, {'loss': 0.1668, 'learning_rate': 1.537971175166297e-05, 'epoch': 3.46, 'step': 12500}, {'loss': 0.1489, 'learning_rate': 1.3993902439024392e-05, 'epoch': 3.6, 'step': 13000}, {'loss': 0.1439, 'learning_rate': 1.260809312638581e-05, 'epoch': 3.74, 'step': 13500}, {'loss': 0.1413, 'learning_rate': 1.122228381374723e-05, 'epoch': 3.88, 'step': 14000}, {'eval_loss': 0.17799262702465057, 'eval_cer': 0.011995299439036829, 'eval_runtime': 2814.9178, 'eval_samples_per_second': 1.282, 'eval_steps_per_second': 0.32, 'epoch': 4.0, 'step': 14432}, {'loss': 0.1193, 'learning_rate': 9.836474501108648e-06, 'epoch': 4.02, 'step': 14500}, {'loss': 0.0904, 'learning_rate': 8.453436807095343e-06, 'epoch': 4.16, 'step': 15000}, {'loss': 0.0822, 'learning_rate': 7.070399113082041e-06, 'epoch': 4.3, 'step': 15500}, {'loss': 0.0675, 'learning_rate': 5.684589800443459e-06, 'epoch': 4.43, 'step': 16000}, {'loss': 0.0606, 'learning_rate': 4.298780487804878e-06, 'epoch': 4.57, 'step': 16500}, {'loss': 0.055, 'learning_rate': 2.912971175166297e-06, 'epoch': 4.71, 'step': 17000}, {'loss': 0.0476, 'learning_rate': 1.5271618625277162e-06, 'epoch': 4.85, 'step': 17500}, {'loss': 0.0513, 'learning_rate': 1.4135254988913526e-07, 'epoch': 4.99, 'step': 18000}, {'eval_loss': 0.10952820628881454, 'eval_cer': 0.007350169619298907, 'eval_runtime': 2798.4707, 'eval_samples_per_second': 1.289, 'eval_steps_per_second': 0.322, 'epoch': 5.0, 'step': 18040}, {'train_runtime': 58940.2961, 'train_samples_per_second': 1.224, 'train_steps_per_second': 0.306, 'total_flos': 9.69366452586519e+19, 'train_loss': 0.575048929558625, 'epoch': 5.0, 'step': 18040}] ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
chainup244/Qwen-Qwen1.5-1.8B-1717562389	chainup244	2024-06-05T04:43:51Z	144	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T04:39:53Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Orion-zhen/Llama3-70B-Orion-Chinese-4bpw-exl2	Orion-zhen	2024-06-05T04:43:35Z	11	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "zh", "en", "license:mit", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "exl2", "region:us" ]	text-generation	2024-06-05T02:40:44Z	--- license: mit language: - zh - en --- # Llama3-70B-Orion-Chinese-4bpw-exl2 这是对[Orion-zhen/Llama3-70B-Orion-Chinese](https://huggingface.co/Orion-zhen/Llama3-70B-Orion-Chinese)的exl2 4bpw量化版采用[Orion-zhen/firefly-exl-calibration](https://huggingface.co/datasets/Orion-zhen/firefly-exl-calibration)作为校准数据集, 以获得较少的中文性能损失并降低出现乱码的概率
hdve/google-gemma-7b-1717562322	hdve	2024-06-05T04:41:22Z	8	0	transformers	[ "transformers", "safetensors", "gemma", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T04:38:45Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
llama-duo/gemma2b-summarize-gpt4o-1k	llama-duo	2024-06-05T04:40:09Z	1	0	peft	[ "peft", "tensorboard", "safetensors", "gemma", "alignment-handbook", "trl", "sft", "generated_from_trainer", "dataset:llama-duo/synth_summarize_dataset_dedup", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "license:gemma", "4-bit", "bitsandbytes", "region:us" ]	null	2024-06-05T04:38:02Z	--- license: gemma library_name: peft tags: - alignment-handbook - trl - sft - generated_from_trainer base_model: google/gemma-2b datasets: - llama-duo/synth_summarize_dataset_dedup model-index: - name: gemma2b-summarize-gpt4o-1k results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # gemma2b-summarize-gpt4o-1k This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.7415 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 3 - gradient_accumulation_steps: 2 - total_train_batch_size: 48 - total_eval_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:---------------:\| \| 2.9975 \| 0.8 \| 2 \| 3.1990 \| \| 2.8744 \| 2.0 \| 5 \| 3.0048 \| \| 2.8744 \| 2.8 \| 7 \| 2.8992 \| \| 2.3833 \| 4.0 \| 10 \| 2.8237 \| \| 2.3833 \| 4.8 \| 12 \| 2.7889 \| \| 2.1436 \| 6.0 \| 15 \| 2.7588 \| \| 2.1436 \| 6.8 \| 17 \| 2.7501 \| \| 2.0522 \| 8.0 \| 20 \| 2.7415 \| ### Framework versions - PEFT 0.11.1 - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1
Jongruk/Custom_tiger_google_vit-base-patch16-224	Jongruk	2024-06-05T04:34:18Z	198	0	transformers	[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-06-05T04:33:50Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
netcat420/MFANN3bv0.12	netcat420	2024-06-05T04:34:12Z	9	0	transformers	[ "transformers", "safetensors", "phi", "text-generation", "en", "dataset:netcat420/MFANN", "arxiv:1910.09700", "license:mit", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T04:00:14Z	--- library_name: transformers license: mit datasets: - netcat420/MFANN language: - en pipeline_tag: text-generation --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
llama-duo/gemma2b-summarize-gemini1_5flash-1k	llama-duo	2024-06-05T04:32:17Z	1	0	peft	[ "peft", "tensorboard", "safetensors", "gemma", "alignment-handbook", "trl", "sft", "generated_from_trainer", "dataset:llama-duo/synth_summarize_dataset_dedup", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "license:gemma", "4-bit", "bitsandbytes", "region:us" ]	null	2024-06-05T04:30:53Z	--- license: gemma library_name: peft tags: - alignment-handbook - trl - sft - generated_from_trainer base_model: google/gemma-2b datasets: - llama-duo/synth_summarize_dataset_dedup model-index: - name: gemma2b-summarize-gemini1_5flash-1k results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # gemma2b-summarize-gemini1_5flash-1k This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.7426 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:---------------:\| \| 2.9957 \| 1.0 \| 2 \| 3.1984 \| \| 2.9957 \| 2.0 \| 4 \| 3.0673 \| \| 2.8525 \| 3.0 \| 6 \| 2.9478 \| \| 2.8525 \| 4.0 \| 8 \| 2.8806 \| \| 2.3323 \| 5.0 \| 10 \| 2.8382 \| \| 2.3323 \| 6.0 \| 12 \| 2.8050 \| \| 2.3323 \| 7.0 \| 14 \| 2.7636 \| \| 2.0887 \| 8.0 \| 16 \| 2.7495 \| \| 2.0887 \| 9.0 \| 18 \| 2.7433 \| \| 1.9997 \| 10.0 \| 20 \| 2.7426 \| ### Framework versions - PEFT 0.11.1 - Transformers 4.40.1 - Pytorch 2.2.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1
warwavn/Custom_tiger_google_vit-base-patch16-224	warwavn	2024-06-05T04:31:14Z	196	0	transformers	[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-06-05T04:30:56Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
duyntnet/bagel-8b-v1.0-imatrix-GGUF	duyntnet	2024-06-05T04:30:48Z	44	0	transformers	[ "transformers", "gguf", "imatrix", "bagel-8b-v1.0", "text-generation", "en", "license:other", "region:us", "conversational" ]	text-generation	2024-06-05T02:10:12Z	--- license: other language: - en pipeline_tag: text-generation inference: false tags: - transformers - gguf - imatrix - bagel-8b-v1.0 --- Quantizations of https://huggingface.co/jondurbin/bagel-8b-v1.0 # From original readme ## Prompt formatting This model uses the llama-3-instruct prompt template, and is provided in the tokenizer config. You can use the `apply_chat_template` method to accurate format prompts, e.g.: ```python import transformers tokenizer = transformers.AutoTokenizer.from_pretrained("jondurbin/bagel-8b-v1.0", trust_remote_code=True) chat = [ {"role": "system", "content": "You are Bob, a friendly AI assistant."}, {"role": "user", "content": "Hello, how are you?"}, {"role": "assistant", "content": "I'm doing great. How can I help you today?"}, {"role": "user", "content": "I'd like to show off how chat templating works!"}, ] print(tokenizer.apply_chat_template(chat, tokenize=False)) ```
Chanchaiw/Custom_tiger_google_vit-base-patch16-224	Chanchaiw	2024-06-05T04:30:45Z	222	0	transformers	[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-06-05T04:30:27Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
panit/Custom_tiger_google_vit-base-patch16-224	panit	2024-06-05T04:30:33Z	196	0	transformers	[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-06-05T04:30:04Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
pankajchouhan07/AccojuntData	pankajchouhan07	2024-06-05T04:30:08Z	0	1	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-05T04:30:08Z	--- license: apache-2.0 ---
ymoslem/whisper-small-ga2en-v5.5-r	ymoslem	2024-06-05T04:29:53Z	19	1	transformers	[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "generated_from_trainer", "ga", "en", "dataset:ymoslem/IWSLT2023-GA-EN", "dataset:ymoslem/FLEURS-GA-EN", "dataset:ymoslem/BitesizeIrish-GA-EN", "dataset:ymoslem/SpokenWords-GA-EN-MTed", "dataset:ymoslem/Tatoeba-Speech-Irish", "dataset:ymoslem/Wikimedia-Speech-Irish", "base_model:openai/whisper-small", "base_model:finetune:openai/whisper-small", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2024-06-04T20:37:43Z	--- language: - ga - en license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - ymoslem/IWSLT2023-GA-EN - ymoslem/FLEURS-GA-EN - ymoslem/BitesizeIrish-GA-EN - ymoslem/SpokenWords-GA-EN-MTed - ymoslem/Tatoeba-Speech-Irish - ymoslem/Wikimedia-Speech-Irish metrics: - bleu - wer model-index: - name: Whisper Small GA-EN Speech Translation results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia type: ymoslem/IWSLT2023-GA-EN metrics: - name: Bleu type: bleu value: 32.44 - name: Wer type: wer value: 63.259792886087354 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Whisper Small GA-EN Speech Translation This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia dataset. It achieves the following results on the evaluation set: - Loss: 1.3690 - Bleu: 32.44 - Chrf: 48.06 - Wer: 63.2598 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.01 - training_steps: 3000 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Bleu \| Chrf \| Wer \| \|:-------------:\|:------:\|:----:\|:---------------:\|:-----:\|:-----:\|:--------:\| \| 2.3655 \| 0.0438 \| 100 \| 1.7709 \| 8.84 \| 26.21 \| 127.7803 \| \| 1.8998 \| 0.0876 \| 200 \| 1.5198 \| 14.9 \| 32.89 \| 99.2796 \| \| 1.5421 \| 0.1313 \| 300 \| 1.3972 \| 16.15 \| 35.77 \| 86.8077 \| \| 1.3154 \| 0.1751 \| 400 \| 1.3412 \| 20.46 \| 39.48 \| 83.0707 \| \| 1.1138 \| 0.2189 \| 500 \| 1.3126 \| 23.16 \| 41.28 \| 74.1108 \| \| 0.9814 \| 0.2627 \| 600 \| 1.3217 \| 25.56 \| 41.67 \| 68.7528 \| \| 0.8897 \| 0.3065 \| 700 \| 1.2859 \| 27.0 \| 43.54 \| 66.3215 \| \| 0.7495 \| 0.3503 \| 800 \| 1.2668 \| 21.71 \| 43.03 \| 75.7767 \| \| 0.7068 \| 0.3940 \| 900 \| 1.2852 \| 17.86 \| 40.88 \| 106.0333 \| \| 0.6002 \| 0.4378 \| 1000 \| 1.2476 \| 24.0 \| 44.26 \| 78.4331 \| \| 0.4989 \| 0.4816 \| 1100 \| 1.2756 \| 28.88 \| 45.57 \| 67.2670 \| \| 0.4464 \| 0.5254 \| 1200 \| 1.2756 \| 27.81 \| 45.53 \| 66.8618 \| \| 0.3883 \| 0.5692 \| 1300 \| 1.2799 \| 29.84 \| 46.03 \| 64.0702 \| \| 0.341 \| 0.6130 \| 1400 \| 1.2693 \| 26.51 \| 43.97 \| 75.3715 \| \| 0.2853 \| 0.6567 \| 1500 \| 1.3310 \| 26.99 \| 45.58 \| 74.0207 \| \| 0.2611 \| 0.7005 \| 1600 \| 1.3022 \| 25.83 \| 44.79 \| 73.4354 \| \| 0.2013 \| 0.7443 \| 1700 \| 1.3266 \| 30.78 \| 46.61 \| 63.6650 \| \| 0.1886 \| 0.7881 \| 1800 \| 1.2943 \| 25.56 \| 45.46 \| 73.7055 \| \| 0.1517 \| 0.8319 \| 1900 \| 1.3193 \| 28.93 \| 45.09 \| 64.3854 \| \| 0.1288 \| 0.8757 \| 2000 \| 1.3567 \| 28.22 \| 44.75 \| 67.6722 \| \| 0.1129 \| 0.9194 \| 2100 \| 1.3431 \| 29.55 \| 46.22 \| 66.2314 \| \| 0.1 \| 0.9632 \| 2200 \| 1.3365 \| 31.46 \| 48.14 \| 64.9257 \| \| 0.0505 \| 1.0070 \| 2300 \| 1.3557 \| 30.37 \| 47.16 \| 64.1153 \| \| 0.0468 \| 1.0508 \| 2400 \| 1.3648 \| 31.57 \| 48.17 \| 62.0891 \| \| 0.0373 \| 1.0946 \| 2500 \| 1.3661 \| 31.56 \| 47.76 \| 64.7456 \| \| 0.0297 \| 1.1384 \| 2600 \| 1.3638 \| 31.13 \| 47.74 \| 64.3854 \| \| 0.0283 \| 1.1821 \| 2700 \| 1.3847 \| 29.98 \| 47.54 \| 65.9613 \| \| 0.0302 \| 1.2259 \| 2800 \| 1.3730 \| 32.32 \| 48.28 \| 64.0252 \| \| 0.0229 \| 1.2697 \| 2900 \| 1.3702 \| 31.47 \| 47.55 \| 65.1508 \| \| 0.0262 \| 1.3135 \| 3000 \| 1.3690 \| 32.44 \| 48.06 \| 63.2598 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.2.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1
AgentBG/Custom_tiger_google_vit-base-patch16-224	AgentBG	2024-06-05T04:27:10Z	222	0	transformers	[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-06-05T04:26:40Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
tsavage68/UTI_L3_1000steps_1e7rate_05beta_CSFTDPO	tsavage68	2024-06-05T04:25:35Z	6	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T04:21:20Z	--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e7rate_05beta_CSFTDPO results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # UTI_L3_1000steps_1e7rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0164 - Rewards/chosen: 1.6699 - Rewards/rejected: -6.1458 - Rewards/accuracies: 0.9900 - Rewards/margins: 7.8157 - Logps/rejected: -75.4864 - Logps/chosen: -29.1393 - Logits/rejected: -1.3321 - Logits/chosen: -1.3145 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-07 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rewards/chosen \| Rewards/rejected \| Rewards/accuracies \| Rewards/margins \| Logps/rejected \| Logps/chosen \| Logits/rejected \| Logits/chosen \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:--------------:\|:----------------:\|:------------------:\|:---------------:\|:--------------:\|:------------:\|:---------------:\|:-------------:\| \| 0.6936 \| 0.3333 \| 25 \| 0.6887 \| -0.0007 \| -0.0109 \| 0.5300 \| 0.0102 \| -63.2166 \| -32.4804 \| -1.3231 \| -1.3079 \| \| 0.6544 \| 0.6667 \| 50 \| 0.6317 \| 0.0212 \| -0.1104 \| 0.8500 \| 0.1316 \| -63.4155 \| -32.4367 \| -1.3229 \| -1.3078 \| \| 0.5537 \| 1.0 \| 75 \| 0.5050 \| 0.0832 \| -0.3693 \| 0.9400 \| 0.4525 \| -63.9333 \| -32.3125 \| -1.3234 \| -1.3083 \| \| 0.3404 \| 1.3333 \| 100 \| 0.3397 \| 0.1907 \| -0.8797 \| 0.9800 \| 1.0704 \| -64.9540 \| -32.0976 \| -1.3239 \| -1.3089 \| \| 0.2191 \| 1.6667 \| 125 \| 0.2217 \| 0.3556 \| -1.4579 \| 0.9900 \| 1.8135 \| -66.1104 \| -31.7678 \| -1.3246 \| -1.3095 \| \| 0.1721 \| 2.0 \| 150 \| 0.1545 \| 0.5057 \| -1.8983 \| 0.9900 \| 2.4040 \| -66.9912 \| -31.4675 \| -1.3248 \| -1.3097 \| \| 0.0763 \| 2.3333 \| 175 \| 0.1116 \| 0.6367 \| -2.3670 \| 0.9900 \| 3.0037 \| -67.9287 \| -31.2056 \| -1.3255 \| -1.3103 \| \| 0.0669 \| 2.6667 \| 200 \| 0.0818 \| 0.7555 \| -2.7499 \| 0.9900 \| 3.5054 \| -68.6945 \| -30.9681 \| -1.3264 \| -1.3111 \| \| 0.0388 \| 3.0 \| 225 \| 0.0620 \| 0.8673 \| -3.2396 \| 0.9900 \| 4.1068 \| -69.6738 \| -30.7445 \| -1.3267 \| -1.3113 \| \| 0.0653 \| 3.3333 \| 250 \| 0.0506 \| 0.9617 \| -3.6047 \| 0.9900 \| 4.5664 \| -70.4041 \| -30.5557 \| -1.3274 \| -1.3119 \| \| 0.0332 \| 3.6667 \| 275 \| 0.0406 \| 1.0595 \| -4.0208 \| 0.9900 \| 5.0803 \| -71.2363 \| -30.3600 \| -1.3276 \| -1.3119 \| \| 0.0522 \| 4.0 \| 300 \| 0.0339 \| 1.1423 \| -4.3687 \| 0.9900 \| 5.5110 \| -71.9320 \| -30.1943 \| -1.3282 \| -1.3123 \| \| 0.005 \| 4.3333 \| 325 \| 0.0293 \| 1.2385 \| -4.6734 \| 0.9900 \| 5.9119 \| -72.5414 \| -30.0020 \| -1.3286 \| -1.3124 \| \| 0.0284 \| 4.6667 \| 350 \| 0.0256 \| 1.3119 \| -4.9072 \| 0.9900 \| 6.2191 \| -73.0091 \| -29.8553 \| -1.3295 \| -1.3132 \| \| 0.0393 \| 5.0 \| 375 \| 0.0229 \| 1.3864 \| -5.1293 \| 0.9900 \| 6.5157 \| -73.4534 \| -29.7063 \| -1.3298 \| -1.3132 \| \| 0.0261 \| 5.3333 \| 400 \| 0.0214 \| 1.4513 \| -5.3049 \| 0.9900 \| 6.7563 \| -73.8046 \| -29.5763 \| -1.3302 \| -1.3135 \| \| 0.0403 \| 5.6667 \| 425 \| 0.0204 \| 1.4964 \| -5.4655 \| 0.9900 \| 6.9619 \| -74.1256 \| -29.4862 \| -1.3304 \| -1.3136 \| \| 0.0197 \| 6.0 \| 450 \| 0.0190 \| 1.5233 \| -5.6170 \| 0.9900 \| 7.1404 \| -74.4287 \| -29.4324 \| -1.3307 \| -1.3137 \| \| 0.0023 \| 6.3333 \| 475 \| 0.0186 \| 1.5672 \| -5.7288 \| 0.9900 \| 7.2960 \| -74.6523 \| -29.3447 \| -1.3310 \| -1.3139 \| \| 0.0391 \| 6.6667 \| 500 \| 0.0181 \| 1.5895 \| -5.8057 \| 0.9900 \| 7.3952 \| -74.8060 \| -29.2999 \| -1.3313 \| -1.3141 \| \| 0.0044 \| 7.0 \| 525 \| 0.0174 \| 1.6125 \| -5.9110 \| 0.9900 \| 7.5235 \| -75.0167 \| -29.2541 \| -1.3314 \| -1.3141 \| \| 0.0034 \| 7.3333 \| 550 \| 0.0178 \| 1.6265 \| -5.9426 \| 0.9900 \| 7.5691 \| -75.0799 \| -29.2260 \| -1.3316 \| -1.3143 \| \| 0.0214 \| 7.6667 \| 575 \| 0.0167 \| 1.6348 \| -6.0154 \| 0.9900 \| 7.6502 \| -75.2254 \| -29.2094 \| -1.3316 \| -1.3143 \| \| 0.0363 \| 8.0 \| 600 \| 0.0166 \| 1.6397 \| -6.0402 \| 0.9900 \| 7.6798 \| -75.2751 \| -29.1997 \| -1.3318 \| -1.3144 \| \| 0.0366 \| 8.3333 \| 625 \| 0.0168 \| 1.6498 \| -6.0578 \| 0.9900 \| 7.7076 \| -75.3102 \| -29.1794 \| -1.3320 \| -1.3145 \| \| 0.0011 \| 8.6667 \| 650 \| 0.0168 \| 1.6607 \| -6.0845 \| 0.9900 \| 7.7452 \| -75.3637 \| -29.1576 \| -1.3319 \| -1.3145 \| \| 0.0043 \| 9.0 \| 675 \| 0.0167 \| 1.6659 \| -6.1131 \| 0.9900 \| 7.7790 \| -75.4209 \| -29.1472 \| -1.3321 \| -1.3146 \| \| 0.0197 \| 9.3333 \| 700 \| 0.0161 \| 1.6703 \| -6.1301 \| 0.9900 \| 7.8004 \| -75.4550 \| -29.1385 \| -1.3320 \| -1.3145 \| \| 0.0186 \| 9.6667 \| 725 \| 0.0165 \| 1.6713 \| -6.1341 \| 0.9900 \| 7.8054 \| -75.4628 \| -29.1364 \| -1.3321 \| -1.3147 \| \| 0.0039 \| 10.0 \| 750 \| 0.0165 \| 1.6700 \| -6.1407 \| 0.9900 \| 7.8106 \| -75.4760 \| -29.1391 \| -1.3321 \| -1.3146 \| \| 0.0005 \| 10.3333 \| 775 \| 0.0164 \| 1.6769 \| -6.1401 \| 0.9900 \| 7.8170 \| -75.4749 \| -29.1251 \| -1.3321 \| -1.3146 \| \| 0.0185 \| 10.6667 \| 800 \| 0.0164 \| 1.6763 \| -6.1561 \| 0.9900 \| 7.8324 \| -75.5069 \| -29.1265 \| -1.3322 \| -1.3146 \| \| 0.0212 \| 11.0 \| 825 \| 0.0162 \| 1.6734 \| -6.1441 \| 0.9900 \| 7.8175 \| -75.4828 \| -29.1321 \| -1.3322 \| -1.3145 \| \| 0.0011 \| 11.3333 \| 850 \| 0.0159 \| 1.6707 \| -6.1474 \| 0.9900 \| 7.8181 \| -75.4894 \| -29.1376 \| -1.3321 \| -1.3145 \| \| 0.0361 \| 11.6667 \| 875 \| 0.0165 \| 1.6746 \| -6.1464 \| 0.9900 \| 7.8209 \| -75.4874 \| -29.1299 \| -1.3322 \| -1.3147 \| \| 0.0029 \| 12.0 \| 900 \| 0.0161 \| 1.6773 \| -6.1406 \| 0.9900 \| 7.8179 \| -75.4759 \| -29.1244 \| -1.3321 \| -1.3146 \| \| 0.019 \| 12.3333 \| 925 \| 0.0163 \| 1.6716 \| -6.1497 \| 0.9900 \| 7.8213 \| -75.4941 \| -29.1358 \| -1.3321 \| -1.3146 \| \| 0.0204 \| 12.6667 \| 950 \| 0.0164 \| 1.6699 \| -6.1458 \| 0.9900 \| 7.8157 \| -75.4864 \| -29.1393 \| -1.3321 \| -1.3145 \| \| 0.0395 \| 13.0 \| 975 \| 0.0164 \| 1.6699 \| -6.1458 \| 0.9900 \| 7.8157 \| -75.4864 \| -29.1393 \| -1.3321 \| -1.3145 \| \| 0.0048 \| 13.3333 \| 1000 \| 0.0164 \| 1.6699 \| -6.1458 \| 0.9900 \| 7.8157 \| -75.4864 \| -29.1393 \| -1.3321 \| -1.3145 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1
ZON8955/uuu_fine_tune_taipower	ZON8955	2024-06-05T04:24:07Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:50:52Z	--- license: apache-2.0 ---
Ponrudee/Custom_tiger_google_vit-base-patch16-224	Ponrudee	2024-06-05T04:21:37Z	218	0	transformers	[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-06-05T04:20:59Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Jongruk/custom-resnet18-model	Jongruk	2024-06-05T04:20:28Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:30:39Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
ChenWeiLi/Taiwan-inquiry_7B_v2.1	ChenWeiLi	2024-06-05T04:19:31Z	13	1	transformers	[ "transformers", "safetensors", "mistral", "text-generation", "Doctor_consultation", "Taiwan", "fine-tuning", "medicine", "conversational", "zh", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-04-17T06:02:25Z	--- license: apache-2.0 language: - zh library_name: transformers pipeline_tag: text-generation tags: - Doctor_consultation - Taiwan - fine-tuning - medicine --- # 🔎 Taiwan-inquiry_7B_v_2.1 <!-- Provide a quick summary of what the model is/does. --> "The model was fine-tuned based on the Breeze-7B-Instruct-v1_0 model using a dataset that includes 614 authentic dialogues from the National Cheng Kung University Hospital. Additionally, 336 synthetic dialogues were included in the training set, carefully crafted to encompass themes drawn from sample questions of the OSCE (臨床技能測驗) sample questions in Taiwan. These synthetic dialogues were generated using GPT-3.5, Gemini-Pro and Breexe-8x7B-Instruct-v0_1. The training process was geared towards simulating verbal exchanges between doctors and patients within a hospital environment." <img src="https://cdn-uploads.huggingface.co/production/uploads/65c07d1b2357c1bded7a92fa/e7QbiYh07kcGwyKniAo0e.png" alt="image/png" style="width:80%; height:auto;"> ************************** Updates ************************** * 2024/04/25 🎉 Released [Taiwan-inquiry_7B_v2.1-awq](https://huggingface.co/ChenWeiLi/Taiwan-inquiry_7B_v2.1-awq) * 2024/04/29 🎉 Released [Taiwan-inquiry_7B_v2.1.gguf](https://huggingface.co/ChenWeiLi/Taiwan-inquiry_7B_v2.1.gguf) ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [Joseph (Chen-Wei) Li](https://www.linkedin.com/in/joseph-li-3a453b231/), researcher assistant from National Taiwan University Hospital. - Model type: A 7B parameter GPT-like model fine-tuned on a combination of private and synthetic dialogue datasets. - Language(s) (NLP): Traditional Chinese (zh-tw) - Finetuned from model : [Breeze-7B-Instruct-v1_0 ](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v1_0) ### Usage of the model - The user can take on the role of a doctor, and the model can engage in conversation with you as if it were a patient. - You can provide the model with a brief patient background in the system prompt, and the model will respond based on that prompt. (using my patient generator: [colab](https://colab.research.google.com/drive/17MSob_tQ2hPtMBL0xOF2zzV6WWe4dEG6?usp=sharing)) - Directly asking the certain disease about the symptoms and the possible therapies.（Warning: It's not medical advice!) ### Model evaluation The model got the TMMLU+ (0 shot) performance using [EleutherAI/lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) with default settings. \|Details on TMMLU+ (0 shot):<br/>Model \| Base Model \| STEM \| Social Science \| Humanities \| Other \| AVG \| \|-----------------------------------------------------\|:---------------------:\|:---------------:\|:--------------:\|:----------:\|:----------:\|:-------:\| \| Taiwan-inquiry_7B_v2.1 \|Breeze-7B-Instruct-v1_0\| 36.06 \| 44.61 \| 37.49 \| 39.61 \| 40.29 \| \| Taiwan-inquiry_7B_v2.0 \|Breeze-7B-Instruct-v0_1\| 36.17 \| 43.59 \| 35.45 \| 37.63 \| 38.95 \| \| Taiwan-inquiry_7B_v1.0 \|Taiwan-LLM-7B-v2.1-chat\| 26.74 \| 29.47 \| 26.83 \| 29.61 \| 28.83 \| ### DEMO - User: <span style="color: orange;">doctor</span> - Chatbot: <span style="color: gray;">patient</span> ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65c07d1b2357c1bded7a92fa/Tp6ZKsGX1f2Qs5FLMFL51.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65c07d1b2357c1bded7a92fa/59A_3WFYl-h34g8XU1XGG.png)
tsavage68/UTI_L3_1000steps_1e8rate_05beta_CSFTDPO	tsavage68	2024-06-05T04:17:12Z	6	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T04:12:57Z	--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e8rate_05beta_CSFTDPO results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # UTI_L3_1000steps_1e8rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6943 - Rewards/chosen: -0.0022 - Rewards/rejected: -0.0014 - Rewards/accuracies: 0.4700 - Rewards/margins: -0.0008 - Logps/rejected: -63.1976 - Logps/chosen: -32.4834 - Logits/rejected: -1.3229 - Logits/chosen: -1.3078 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-08 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rewards/chosen \| Rewards/rejected \| Rewards/accuracies \| Rewards/margins \| Logps/rejected \| Logps/chosen \| Logits/rejected \| Logits/chosen \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:--------------:\|:----------------:\|:------------------:\|:---------------:\|:--------------:\|:------------:\|:---------------:\|:-------------:\| \| 0.6937 \| 0.3333 \| 25 \| 0.6957 \| -0.0013 \| 0.0035 \| 0.0500 \| -0.0048 \| -63.1876 \| -32.4816 \| -1.3228 \| -1.3077 \| \| 0.6934 \| 0.6667 \| 50 \| 0.6925 \| -0.0026 \| -0.0053 \| 0.5100 \| 0.0027 \| -63.2053 \| -32.4843 \| -1.3228 \| -1.3077 \| \| 0.6898 \| 1.0 \| 75 \| 0.6961 \| -0.0017 \| 0.0030 \| 0.4800 \| -0.0047 \| -63.1886 \| -32.4823 \| -1.3230 \| -1.3078 \| \| 0.6855 \| 1.3333 \| 100 \| 0.6937 \| 0.0021 \| 0.0020 \| 0.5200 \| 0.0001 \| -63.1908 \| -32.4748 \| -1.3230 \| -1.3079 \| \| 0.6852 \| 1.6667 \| 125 \| 0.6971 \| -0.0047 \| 0.0016 \| 0.4200 \| -0.0062 \| -63.1916 \| -32.4884 \| -1.3230 \| -1.3078 \| \| 0.6879 \| 2.0 \| 150 \| 0.6905 \| 0.0038 \| -0.0031 \| 0.4500 \| 0.0069 \| -63.2009 \| -32.4715 \| -1.3231 \| -1.3079 \| \| 0.6957 \| 2.3333 \| 175 \| 0.6911 \| -0.0001 \| -0.0058 \| 0.5200 \| 0.0057 \| -63.2062 \| -32.4793 \| -1.3230 \| -1.3079 \| \| 0.6988 \| 2.6667 \| 200 \| 0.6929 \| -0.0035 \| -0.0053 \| 0.5300 \| 0.0018 \| -63.2052 \| -32.4859 \| -1.3229 \| -1.3078 \| \| 0.6926 \| 3.0 \| 225 \| 0.6903 \| 0.0001 \| -0.0071 \| 0.5 \| 0.0072 \| -63.2088 \| -32.4787 \| -1.3230 \| -1.3078 \| \| 0.6895 \| 3.3333 \| 250 \| 0.6896 \| -0.0014 \| -0.0101 \| 0.5 \| 0.0087 \| -63.2149 \| -32.4818 \| -1.3230 \| -1.3079 \| \| 0.6988 \| 3.6667 \| 275 \| 0.6932 \| -0.0029 \| -0.0044 \| 0.5 \| 0.0015 \| -63.2034 \| -32.4847 \| -1.3231 \| -1.3079 \| \| 0.6719 \| 4.0 \| 300 \| 0.6895 \| -0.0022 \| -0.0107 \| 0.4900 \| 0.0085 \| -63.2161 \| -32.4833 \| -1.3230 \| -1.3079 \| \| 0.6988 \| 4.3333 \| 325 \| 0.6886 \| 0.0061 \| -0.0045 \| 0.5100 \| 0.0106 \| -63.2038 \| -32.4668 \| -1.3231 \| -1.3080 \| \| 0.6859 \| 4.6667 \| 350 \| 0.6869 \| 0.0014 \| -0.0126 \| 0.5500 \| 0.0139 \| -63.2198 \| -32.4762 \| -1.3231 \| -1.3080 \| \| 0.6922 \| 5.0 \| 375 \| 0.6888 \| -0.0004 \| -0.0102 \| 0.5 \| 0.0097 \| -63.2150 \| -32.4799 \| -1.3230 \| -1.3079 \| \| 0.6937 \| 5.3333 \| 400 \| 0.6875 \| 0.0028 \| -0.0102 \| 0.5400 \| 0.0130 \| -63.2150 \| -32.4734 \| -1.3231 \| -1.3080 \| \| 0.6773 \| 5.6667 \| 425 \| 0.6857 \| 0.0025 \| -0.0143 \| 0.5300 \| 0.0168 \| -63.2233 \| -32.4741 \| -1.3228 \| -1.3078 \| \| 0.684 \| 6.0 \| 450 \| 0.6900 \| 0.0039 \| -0.0036 \| 0.5400 \| 0.0075 \| -63.2019 \| -32.4713 \| -1.3231 \| -1.3079 \| \| 0.6914 \| 6.3333 \| 475 \| 0.6902 \| 0.0001 \| -0.0078 \| 0.5300 \| 0.0079 \| -63.2103 \| -32.4789 \| -1.3230 \| -1.3079 \| \| 0.6879 \| 6.6667 \| 500 \| 0.6871 \| 0.0049 \| -0.0084 \| 0.5300 \| 0.0133 \| -63.2115 \| -32.4691 \| -1.3229 \| -1.3078 \| \| 0.6934 \| 7.0 \| 525 \| 0.6896 \| 0.0039 \| -0.0046 \| 0.4900 \| 0.0085 \| -63.2039 \| -32.4712 \| -1.3230 \| -1.3079 \| \| 0.6887 \| 7.3333 \| 550 \| 0.6901 \| 0.0037 \| -0.0042 \| 0.5200 \| 0.0079 \| -63.2031 \| -32.4717 \| -1.3230 \| -1.3079 \| \| 0.6863 \| 7.6667 \| 575 \| 0.6909 \| -0.0015 \| -0.0071 \| 0.5800 \| 0.0057 \| -63.2090 \| -32.4819 \| -1.3230 \| -1.3079 \| \| 0.6809 \| 8.0 \| 600 \| 0.6895 \| -0.0005 \| -0.0093 \| 0.5500 \| 0.0088 \| -63.2133 \| -32.4801 \| -1.3229 \| -1.3077 \| \| 0.6879 \| 8.3333 \| 625 \| 0.6906 \| 0.0042 \| -0.0019 \| 0.5200 \| 0.0061 \| -63.1984 \| -32.4706 \| -1.3230 \| -1.3079 \| \| 0.6844 \| 8.6667 \| 650 \| 0.6865 \| -0.0004 \| -0.0156 \| 0.5100 \| 0.0152 \| -63.2259 \| -32.4798 \| -1.3229 \| -1.3079 \| \| 0.6945 \| 9.0 \| 675 \| 0.6899 \| -0.0047 \| -0.0124 \| 0.5500 \| 0.0077 \| -63.2195 \| -32.4884 \| -1.3230 \| -1.3079 \| \| 0.6918 \| 9.3333 \| 700 \| 0.6859 \| 0.0034 \| -0.0127 \| 0.5400 \| 0.0160 \| -63.2200 \| -32.4723 \| -1.3230 \| -1.3079 \| \| 0.6848 \| 9.6667 \| 725 \| 0.6909 \| -0.0053 \| -0.0113 \| 0.5200 \| 0.0060 \| -63.2172 \| -32.4896 \| -1.3229 \| -1.3078 \| \| 0.6801 \| 10.0 \| 750 \| 0.6915 \| 0.0025 \| -0.0025 \| 0.5300 \| 0.0049 \| -63.1997 \| -32.4741 \| -1.3229 \| -1.3078 \| \| 0.684 \| 10.3333 \| 775 \| 0.6939 \| -0.0003 \| -0.0002 \| 0.4900 \| -0.0001 \| -63.1951 \| -32.4797 \| -1.3229 \| -1.3078 \| \| 0.6891 \| 10.6667 \| 800 \| 0.6936 \| -0.0012 \| -0.0017 \| 0.4900 \| 0.0005 \| -63.1981 \| -32.4814 \| -1.3229 \| -1.3078 \| \| 0.6883 \| 11.0 \| 825 \| 0.6943 \| -0.0022 \| -0.0014 \| 0.4700 \| -0.0008 \| -63.1976 \| -32.4834 \| -1.3229 \| -1.3078 \| \| 0.6969 \| 11.3333 \| 850 \| 0.6943 \| -0.0022 \| -0.0014 \| 0.4700 \| -0.0008 \| -63.1976 \| -32.4834 \| -1.3229 \| -1.3078 \| \| 0.6984 \| 11.6667 \| 875 \| 0.6943 \| -0.0022 \| -0.0014 \| 0.4700 \| -0.0008 \| -63.1976 \| -32.4834 \| -1.3229 \| -1.3078 \| \| 0.6937 \| 12.0 \| 900 \| 0.6943 \| -0.0022 \| -0.0014 \| 0.4700 \| -0.0008 \| -63.1976 \| -32.4834 \| -1.3229 \| -1.3078 \| \| 0.684 \| 12.3333 \| 925 \| 0.6943 \| -0.0022 \| -0.0014 \| 0.4700 \| -0.0008 \| -63.1976 \| -32.4834 \| -1.3229 \| -1.3078 \| \| 0.682 \| 12.6667 \| 950 \| 0.6943 \| -0.0022 \| -0.0014 \| 0.4700 \| -0.0008 \| -63.1976 \| -32.4834 \| -1.3229 \| -1.3078 \| \| 0.6863 \| 13.0 \| 975 \| 0.6943 \| -0.0022 \| -0.0014 \| 0.4700 \| -0.0008 \| -63.1976 \| -32.4834 \| -1.3229 \| -1.3078 \| \| 0.6836 \| 13.3333 \| 1000 \| 0.6943 \| -0.0022 \| -0.0014 \| 0.4700 \| -0.0008 \| -63.1976 \| -32.4834 \| -1.3229 \| -1.3078 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1
PhillipGuo/hp-lat-llama-PCA-epsilon6.0-pgd_layer8_16-def_layer8-wikitext-28	PhillipGuo	2024-06-05T04:14:35Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T04:14:26Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
panit/custom-resnet18-model	panit	2024-06-05T04:12:32Z	81	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:59:11Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
rishisim/q-FrozenLake-v1-4x4-noSlippery	rishisim	2024-06-05T04:11:25Z	0	0	null	[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2024-06-05T04:08:17Z	--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # Q-Learning Agent playing1 FrozenLake-v1 This is a trained model of a Q-Learning agent playing FrozenLake-v1 . ## Usage ```python model = load_from_hub(repo_id="rishisim/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
kanitthong/custom-resnet18-model	kanitthong	2024-06-05T04:10:07Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T04:08:41Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
warwavn/custom-resnet18-model	warwavn	2024-06-05T04:08:07Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:59:35Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
kikikara/llama_with_eeve_the_third	kikikara	2024-06-05T04:05:00Z	142	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "trl", "sft", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T04:03:39Z	--- library_name: transformers tags: - trl - sft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
WriLee/custom-resnet18-model	WriLee	2024-06-05T04:04:47Z	80	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:55:11Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
richardkelly/Qwen-Qwen1.5-1.8B-1717554065	richardkelly	2024-06-05T04:04:43Z	198	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T02:21:05Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Preeda/custom-resnet18-model-2	Preeda	2024-06-05T04:04:43Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T04:04:34Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
Tsover/custom-resnet18-model	Tsover	2024-06-05T04:03:13Z	81	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:51:30Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
PhillipGuo/hp-lat-llama-PCA-epsilon6.0-pgd_layer8_16-def_layer8-wikitext-27	PhillipGuo	2024-06-05T04:02:53Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T04:02:44Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-28	PhillipGuo	2024-06-05T04:02:40Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T04:02:30Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
superdavidyeh/uuu_fine_tune_gpt2	superdavidyeh	2024-06-05T04:01:34Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:02:18Z	--- license: apache-2.0 ---
thanaporn/kwang-resnet18-model	thanaporn	2024-06-05T04:01:32Z	81	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:58:11Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
cutedogspark/uuu_fine_tune_gpt2	cutedogspark	2024-06-05T04:00:19Z	145	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:02:14Z	--- license: apache-2.0 ---
temporary0-0name/pragna_with_adapt2	temporary0-0name	2024-06-05T04:00:11Z	128	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:46:59Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-27	PhillipGuo	2024-06-05T03:59:11Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:59:01Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
PhillipGuo/hp-lat-llama-PCA-epsilon0.5-pgd_layer8_16-def_layer8-wikitext-27	PhillipGuo	2024-06-05T03:59:10Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:59:01Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
tsavage68/UTI_M2_50steps_1e6rate_05beta_CSFTDPO	tsavage68	2024-06-05T03:58:05Z	6	0	transformers	[ "transformers", "safetensors", "mistral", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_M2_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_M2_1000steps_1e5rate_SFT", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:52:41Z	--- license: apache-2.0 base_model: tsavage68/UTI_M2_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_M2_50steps_1e6rate_05beta_CSFTDPO results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # UTI_M2_50steps_1e6rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_M2_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_M2_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0694 - Rewards/chosen: 1.8275 - Rewards/rejected: -9.1239 - Rewards/accuracies: 0.9000 - Rewards/margins: 10.9514 - Logps/rejected: -62.4139 - Logps/chosen: -16.6395 - Logits/rejected: -3.8318 - Logits/chosen: -3.7514 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-06 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 50 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rewards/chosen \| Rewards/rejected \| Rewards/accuracies \| Rewards/margins \| Logps/rejected \| Logps/chosen \| Logits/rejected \| Logits/chosen \| \|:-------------:\|:------:\|:----:\|:---------------:\|:--------------:\|:----------------:\|:------------------:\|:---------------:\|:--------------:\|:------------:\|:---------------:\|:-------------:\| \| 0.314 \| 0.3333 \| 25 \| 0.1006 \| 1.1509 \| -3.4985 \| 0.9000 \| 4.6494 \| -51.1631 \| -17.9927 \| -3.8266 \| -3.7515 \| \| 0.0175 \| 0.6667 \| 50 \| 0.0694 \| 1.8275 \| -9.1239 \| 0.9000 \| 10.9514 \| -62.4139 \| -16.6395 \| -3.8318 \| -3.7514 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1
Manirathinam21/zephyr-7b-finetuned-support-chatbot	Manirathinam21	2024-06-05T03:57:45Z	1	0	peft	[ "peft", "tensorboard", "safetensors", "trl", "sft", "generated_from_trainer", "base_model:TheBloke/zephyr-7B-alpha-GPTQ", "base_model:adapter:TheBloke/zephyr-7B-alpha-GPTQ", "license:mit", "region:us" ]	null	2024-06-05T03:24:54Z	--- license: mit library_name: peft tags: - trl - sft - generated_from_trainer base_model: TheBloke/zephyr-7B-alpha-GPTQ model-index: - name: zephyr-7b-finetuned-support-chatbot results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # zephyr-7b-finetuned-support-chatbot This model is a fine-tuned version of [TheBloke/zephyr-7B-alpha-GPTQ](https://huggingface.co/TheBloke/zephyr-7B-alpha-GPTQ) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 250 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.11.1 - Transformers 4.41.1 - Pytorch 2.3.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1
brax2005/Brax	brax2005	2024-06-05T03:55:24Z	0	0	fastai	[ "fastai", "climate", "text2text-generation", "ak", "dataset:H-D-T/Buzz", "arxiv:1910.09700", "license:bigscience-openrail-m", "region:us" ]	text2text-generation	2024-06-05T03:54:20Z	--- license: bigscience-openrail-m datasets: - H-D-T/Buzz language: - ak metrics: - cer library_name: fastai pipeline_tag: text2text-generation tags: - climate --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Allister7274/GIDEONunit	Allister7274	2024-06-05T03:48:18Z	0	0	null	[ "region:us" ]	null	2024-06-05T03:34:12Z	--- license: wtfpl datasets: - openbmb/RLAIF-V-Dataset language: - en metrics: - character tags: - documentation ---Adio-To-Text Text-To-Audio Voice-Analsis import speech_recognition as sr class GIDEONunit: def __init__(self): pass def transcribe_audio(self, audio_file): recognizer = sr.Recognizer() # Load audio file with sr.AudioFile(audio_file) as source: audio_data = recognizer.record(source) try: # Convert speech to text text = recognizer.recognize_google(audio_data) return text except sr.UnknownValueError: print("GIDEONunit could not understand the audio.") return "" except sr.RequestError as e: print(f"Could not request results from Google Speech Recognition service; {e}") return "" def create_documentation(self, audio_file, output_file): # Transcribe audio to text text = self.transcribe_audio(audio_file) # Write text to output file with open(output_file, "w") as f: f.write(text) # Example usage if __name__ == "__main__": gideon = GIDEONunit() audio_file = "input_audio.wav" output_file = "output_documentation.txt" gideon.create_documentation(audio_file, output_file)
RyanTsai0321/uuu_fine_tune_gpt2	RyanTsai0321	2024-06-05T03:45:50Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:01:04Z	--- license: apache-2.0 ---
siaowei-test/uuu_fine_tune_gpt2	siaowei-test	2024-06-05T03:45:28Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:17:53Z	--- license: apache-2.0 ---
ZaqAttack/bert-finetuned-ner	ZaqAttack	2024-06-05T03:45:10Z	62	0	transformers	[ "transformers", "tf", "bert", "token-classification", "generated_from_keras_callback", "base_model:google-bert/bert-base-cased", "base_model:finetune:google-bert/bert-base-cased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	token-classification	2024-06-04T22:24:15Z	--- license: apache-2.0 base_model: bert-base-cased tags: - generated_from_keras_callback model-index: - name: ZaqAttack/bert-finetuned-ner results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # ZaqAttack/bert-finetuned-ner This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0477 - Validation Loss: 0.0576 - Epoch: 1 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2634, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: mixed_float16 ### Training results \| Train Loss \| Validation Loss \| Epoch \| \|:----------:\|:---------------:\|:-----:\| \| 0.1778 \| 0.0689 \| 0 \| \| 0.0477 \| 0.0576 \| 1 \| ### Framework versions - Transformers 4.41.1 - TensorFlow 2.15.0 - Datasets 2.19.2 - Tokenizers 0.19.1
Felix-Jas/uuu_fine_tune_gpt2	Felix-Jas	2024-06-05T03:44:55Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:18:18Z	--- license: apache-2.0 ---
PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-26	PhillipGuo	2024-06-05T03:44:45Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:44:35Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
PhillipGuo/hp-lat-llama-PCA-epsilon0.5-pgd_layer8_16-def_layer8-wikitext-26	PhillipGuo	2024-06-05T03:43:57Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:43:47Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
XBLUECATX/KeypointRCNN_Pretrained	XBLUECATX	2024-06-05T03:41:45Z	0	0	null	[ "license:llama3", "region:us" ]	null	2024-06-05T03:38:29Z	--- license: llama3 --- This weight is pre-trained for Keypoint Detection Tutorial usage. Incase the students cannot train due to hardware limitation or other issues. https://github.com/xxBLUECATxx/Simple_Keypoint_Detect
0xfaskety/Qwen-Qwen1.5-7B-1717558334	0xfaskety	2024-06-05T03:38:58Z	8	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:32:17Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
PhillipGuo/hp-lat-llama-PCA-epsilon6.0-pgd_layer8_16-def_layer8-wikitext-25	PhillipGuo	2024-06-05T03:36:18Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:36:08Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
gaminwu/gpt2_finetuned_medical	gaminwu	2024-06-05T03:35:36Z	145	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:34:27Z	--- license: apache-2.0 ---
DuridMing/uuu_fine_tune_taipower	DuridMing	2024-06-05T03:35:25Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:01:53Z	--- license: apache-2.0 ---
JJ1970/uuu_fine_tune_taipower	JJ1970	2024-06-05T03:35:06Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:27:38Z	--- license: apache-2.0 ---
Chanchaiw/custom-resnet18-model	Chanchaiw	2024-06-05T03:32:52Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:58:51Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
Preeda/custom-resnet18-model-1	Preeda	2024-06-05T03:30:45Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:30:36Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-25	PhillipGuo	2024-06-05T03:28:54Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:28:44Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Preeda/custom-resnet18-model	Preeda	2024-06-05T03:28:14Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:04:46Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
Airtan23/custom-resnet18-model-ex2	Airtan23	2024-06-05T03:27:18Z	80	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:27:11Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
siaowei-test/uuu_fine_tune_taipower	siaowei-test	2024-06-05T03:27:15Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:14:49Z	--- license: apache-2.0 ---
Felix-Jas/uuu_fine_tune_taipower	Felix-Jas	2024-06-05T03:25:49Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:18:06Z	--- license: apache-2.0 ---
PhillipGuo/hp-lat-llama-PCA-epsilon0.5-pgd_layer8_16-def_layer8-wikitext-25	PhillipGuo	2024-06-05T03:25:20Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:25:11Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
PhillipGuo/hp-lat-llama-PCA-epsilon3.0-pgd_layer8_16-def_layer8-wikitext-24	PhillipGuo	2024-06-05T03:22:42Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:22:33Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Hannanana/uuu_fine_tune_taipower	Hannanana	2024-06-05T03:21:52Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:00:38Z	--- license: apache-2.0 ---
nuttcutee/nut-resnet18-model	nuttcutee	2024-06-05T03:21:48Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:59:33Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
tsavage68/UTI_L3_1000steps_1e8rate_03beta_CSFTDPO	tsavage68	2024-06-05T03:21:22Z	7	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:16:45Z	--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e8rate_03beta_CSFTDPO results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # UTI_L3_1000steps_1e8rate_03beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6892 - Rewards/chosen: 0.0019 - Rewards/rejected: -0.0064 - Rewards/accuracies: 0.6200 - Rewards/margins: 0.0083 - Logps/rejected: -63.2161 - Logps/chosen: -32.4727 - Logits/rejected: -1.3229 - Logits/chosen: -1.3077 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-08 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rewards/chosen \| Rewards/rejected \| Rewards/accuracies \| Rewards/margins \| Logps/rejected \| Logps/chosen \| Logits/rejected \| Logits/chosen \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:--------------:\|:----------------:\|:------------------:\|:---------------:\|:--------------:\|:------------:\|:---------------:\|:-------------:\| \| 0.6937 \| 0.3333 \| 25 \| 0.6946 \| -0.0008 \| 0.0021 \| 0.0600 \| -0.0029 \| -63.1876 \| -32.4816 \| -1.3229 \| -1.3077 \| \| 0.6914 \| 0.6667 \| 50 \| 0.6957 \| -0.0038 \| 0.0008 \| 0.4400 \| -0.0046 \| -63.1920 \| -32.4917 \| -1.3228 \| -1.3077 \| \| 0.691 \| 1.0 \| 75 \| 0.6939 \| -0.0059 \| -0.0048 \| 0.4400 \| -0.0011 \| -63.2107 \| -32.4987 \| -1.3231 \| -1.3080 \| \| 0.6895 \| 1.3333 \| 100 \| 0.6936 \| -0.0030 \| -0.0027 \| 0.4600 \| -0.0004 \| -63.2035 \| -32.4892 \| -1.3230 \| -1.3079 \| \| 0.6875 \| 1.6667 \| 125 \| 0.6931 \| 0.0025 \| 0.0020 \| 0.5100 \| 0.0006 \| -63.1881 \| -32.4706 \| -1.3230 \| -1.3079 \| \| 0.6949 \| 2.0 \| 150 \| 0.6956 \| 0.0004 \| 0.0046 \| 0.4400 \| -0.0042 \| -63.1792 \| -32.4777 \| -1.3229 \| -1.3078 \| \| 0.6996 \| 2.3333 \| 175 \| 0.6922 \| -0.0011 \| -0.0034 \| 0.5 \| 0.0023 \| -63.2060 \| -32.4828 \| -1.3229 \| -1.3078 \| \| 0.691 \| 2.6667 \| 200 \| 0.6933 \| 0.0001 \| 0.0001 \| 0.5200 \| -0.0000 \| -63.1942 \| -32.4786 \| -1.3230 \| -1.3079 \| \| 0.6879 \| 3.0 \| 225 \| 0.6925 \| -0.0011 \| -0.0031 \| 0.5400 \| 0.0020 \| -63.2049 \| -32.4826 \| -1.3230 \| -1.3079 \| \| 0.691 \| 3.3333 \| 250 \| 0.6907 \| 0.0015 \| -0.0040 \| 0.4900 \| 0.0055 \| -63.2080 \| -32.4741 \| -1.3229 \| -1.3079 \| \| 0.6953 \| 3.6667 \| 275 \| 0.6924 \| 0.0027 \| 0.0008 \| 0.4700 \| 0.0019 \| -63.1921 \| -32.4699 \| -1.3229 \| -1.3078 \| \| 0.6906 \| 4.0 \| 300 \| 0.6906 \| -0.0010 \| -0.0066 \| 0.5200 \| 0.0056 \| -63.2167 \| -32.4825 \| -1.3230 \| -1.3079 \| \| 0.6973 \| 4.3333 \| 325 \| 0.6879 \| 0.0027 \| -0.0083 \| 0.6100 \| 0.0111 \| -63.2224 \| -32.4699 \| -1.3229 \| -1.3078 \| \| 0.6887 \| 4.6667 \| 350 \| 0.6875 \| 0.0051 \| -0.0066 \| 0.5900 \| 0.0118 \| -63.2168 \| -32.4619 \| -1.3230 \| -1.3078 \| \| 0.6891 \| 5.0 \| 375 \| 0.6887 \| 0.0018 \| -0.0076 \| 0.5800 \| 0.0093 \| -63.2199 \| -32.4732 \| -1.3228 \| -1.3077 \| \| 0.6961 \| 5.3333 \| 400 \| 0.6906 \| 0.0023 \| -0.0033 \| 0.5700 \| 0.0055 \| -63.2056 \| -32.4714 \| -1.3230 \| -1.3079 \| \| 0.6848 \| 5.6667 \| 425 \| 0.6902 \| 0.0003 \| -0.0061 \| 0.5200 \| 0.0064 \| -63.2151 \| -32.4779 \| -1.3229 \| -1.3078 \| \| 0.6855 \| 6.0 \| 450 \| 0.6883 \| 0.0021 \| -0.0083 \| 0.5600 \| 0.0104 \| -63.2224 \| -32.4722 \| -1.3230 \| -1.3079 \| \| 0.6898 \| 6.3333 \| 475 \| 0.6922 \| -0.0013 \| -0.0038 \| 0.5300 \| 0.0026 \| -63.2075 \| -32.4832 \| -1.3229 \| -1.3078 \| \| 0.6887 \| 6.6667 \| 500 \| 0.6905 \| 0.0023 \| -0.0037 \| 0.5400 \| 0.0060 \| -63.2071 \| -32.4715 \| -1.3229 \| -1.3078 \| \| 0.6918 \| 7.0 \| 525 \| 0.6862 \| 0.0033 \| -0.0110 \| 0.5900 \| 0.0144 \| -63.2315 \| -32.4679 \| -1.3231 \| -1.3080 \| \| 0.6871 \| 7.3333 \| 550 \| 0.6902 \| 0.0020 \| -0.0043 \| 0.5300 \| 0.0063 \| -63.2090 \| -32.4723 \| -1.3229 \| -1.3078 \| \| 0.6879 \| 7.6667 \| 575 \| 0.6927 \| -0.0028 \| -0.0041 \| 0.4800 \| 0.0013 \| -63.2085 \| -32.4885 \| -1.3229 \| -1.3078 \| \| 0.6793 \| 8.0 \| 600 \| 0.6925 \| -0.0004 \| -0.0022 \| 0.4600 \| 0.0018 \| -63.2021 \| -32.4805 \| -1.3230 \| -1.3079 \| \| 0.6918 \| 8.3333 \| 625 \| 0.6904 \| 0.0009 \| -0.0052 \| 0.5200 \| 0.0060 \| -63.2119 \| -32.4762 \| -1.3230 \| -1.3079 \| \| 0.6887 \| 8.6667 \| 650 \| 0.6896 \| 0.0015 \| -0.0061 \| 0.5500 \| 0.0076 \| -63.2150 \| -32.4739 \| -1.3229 \| -1.3078 \| \| 0.6965 \| 9.0 \| 675 \| 0.6905 \| -0.0013 \| -0.0072 \| 0.5600 \| 0.0060 \| -63.2188 \| -32.4833 \| -1.3230 \| -1.3078 \| \| 0.6895 \| 9.3333 \| 700 \| 0.6877 \| 0.0038 \| -0.0076 \| 0.6200 \| 0.0114 \| -63.2200 \| -32.4662 \| -1.3229 \| -1.3078 \| \| 0.6855 \| 9.6667 \| 725 \| 0.6891 \| 0.0014 \| -0.0074 \| 0.5500 \| 0.0087 \| -63.2192 \| -32.4744 \| -1.3229 \| -1.3078 \| \| 0.6871 \| 10.0 \| 750 \| 0.6879 \| 0.0033 \| -0.0077 \| 0.5900 \| 0.0110 \| -63.2204 \| -32.4679 \| -1.3230 \| -1.3078 \| \| 0.6887 \| 10.3333 \| 775 \| 0.6881 \| 0.0034 \| -0.0072 \| 0.6200 \| 0.0106 \| -63.2186 \| -32.4675 \| -1.3229 \| -1.3077 \| \| 0.693 \| 10.6667 \| 800 \| 0.6890 \| 0.0023 \| -0.0065 \| 0.6200 \| 0.0088 \| -63.2163 \| -32.4715 \| -1.3229 \| -1.3078 \| \| 0.6875 \| 11.0 \| 825 \| 0.6892 \| 0.0019 \| -0.0064 \| 0.6200 \| 0.0083 \| -63.2161 \| -32.4727 \| -1.3229 \| -1.3077 \| \| 0.6895 \| 11.3333 \| 850 \| 0.6892 \| 0.0019 \| -0.0064 \| 0.6200 \| 0.0083 \| -63.2161 \| -32.4727 \| -1.3229 \| -1.3077 \| \| 0.6887 \| 11.6667 \| 875 \| 0.6892 \| 0.0019 \| -0.0064 \| 0.6200 \| 0.0083 \| -63.2161 \| -32.4727 \| -1.3229 \| -1.3077 \| \| 0.6918 \| 12.0 \| 900 \| 0.6892 \| 0.0019 \| -0.0064 \| 0.6200 \| 0.0083 \| -63.2161 \| -32.4727 \| -1.3229 \| -1.3077 \| \| 0.6918 \| 12.3333 \| 925 \| 0.6892 \| 0.0019 \| -0.0064 \| 0.6200 \| 0.0083 \| -63.2161 \| -32.4727 \| -1.3229 \| -1.3077 \| \| 0.6816 \| 12.6667 \| 950 \| 0.6892 \| 0.0019 \| -0.0064 \| 0.6200 \| 0.0083 \| -63.2161 \| -32.4727 \| -1.3229 \| -1.3077 \| \| 0.6883 \| 13.0 \| 975 \| 0.6892 \| 0.0019 \| -0.0064 \| 0.6200 \| 0.0083 \| -63.2161 \| -32.4727 \| -1.3229 \| -1.3077 \| \| 0.6883 \| 13.3333 \| 1000 \| 0.6892 \| 0.0019 \| -0.0064 \| 0.6200 \| 0.0083 \| -63.2161 \| -32.4727 \| -1.3229 \| -1.3077 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1
Ponrudee/custom-resnet18-model	Ponrudee	2024-06-05T03:20:24Z	80	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:59:57Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-24	PhillipGuo	2024-06-05T03:17:42Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:17:33Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
mradermacher/Shiki-m7-GGUF	mradermacher	2024-06-05T03:17:15Z	19	0	transformers	[ "transformers", "gguf", "en", "base_model:Sao10K/Shiki-m7", "base_model:quantized:Sao10K/Shiki-m7", "license:cc-by-nc-4.0", "endpoints_compatible", "region:us" ]	null	2024-06-04T16:35:42Z	--- base_model: Sao10K/Shiki-m7 language: - en library_name: transformers license: cc-by-nc-4.0 quantized_by: mradermacher --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> static quants of https://huggingface.co/Sao10K/Shiki-m7 <!-- provided-files --> weighted/imatrix quants are available at https://huggingface.co/mradermacher/Shiki-m7-i1-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) \| Link \| Type \| Size/GB \| Notes \| \|:-----\|:-----\|--------:\|:------\| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q2_K.gguf) \| Q2_K \| 2.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.IQ3_XS.gguf) \| IQ3_XS \| 3.1 \| \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q3_K_S.gguf) \| Q3_K_S \| 3.3 \| \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.IQ3_S.gguf) \| IQ3_S \| 3.3 \| beats Q3_K* \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.IQ3_M.gguf) \| IQ3_M \| 3.4 \| \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q3_K_M.gguf) \| Q3_K_M \| 3.6 \| lower quality \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q3_K_L.gguf) \| Q3_K_L \| 3.9 \| \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.IQ4_XS.gguf) \| IQ4_XS \| 4.0 \| \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q4_K_S.gguf) \| Q4_K_S \| 4.2 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q4_K_M.gguf) \| Q4_K_M \| 4.5 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q5_K_S.gguf) \| Q5_K_S \| 5.1 \| \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q5_K_M.gguf) \| Q5_K_M \| 5.2 \| \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q6_K.gguf) \| Q6_K \| 6.0 \| very good quality \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q8_0.gguf) \| Q8_0 \| 7.8 \| fast, best quality \| \| [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.f16.gguf) \| f16 \| 14.6 \| 16 bpw, overkill \| Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. <!-- end -->
tsavage68/UTI_L3_1000steps_1e5rate_05beta_CSFTDPO	tsavage68	2024-06-05T03:14:51Z	6	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:10:24Z	--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e5rate_05beta_CSFTDPO results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # UTI_L3_1000steps_1e5rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0069 - Rewards/chosen: 2.5286 - Rewards/rejected: -48.6639 - Rewards/accuracies: 0.9900 - Rewards/margins: 51.1926 - Logps/rejected: -160.5225 - Logps/chosen: -27.4217 - Logits/rejected: -1.3535 - Logits/chosen: -1.3136 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rewards/chosen \| Rewards/rejected \| Rewards/accuracies \| Rewards/margins \| Logps/rejected \| Logps/chosen \| Logits/rejected \| Logits/chosen \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:--------------:\|:----------------:\|:------------------:\|:---------------:\|:--------------:\|:------------:\|:---------------:\|:-------------:\| \| 0.0 \| 0.6667 \| 50 \| 0.0071 \| 1.6538 \| -15.9005 \| 0.9900 \| 17.5543 \| -94.9957 \| -29.1714 \| -1.3772 \| -1.3510 \| \| 0.0173 \| 1.3333 \| 100 \| 0.1641 \| 5.8391 \| -14.1581 \| 0.9100 \| 19.9972 \| -91.5108 \| -20.8008 \| -1.4149 \| -1.3894 \| \| 0.0347 \| 2.0 \| 150 \| 0.0069 \| 2.5321 \| -48.6719 \| 0.9900 \| 51.2040 \| -160.5385 \| -27.4149 \| -1.3535 \| -1.3136 \| \| 0.0 \| 2.6667 \| 200 \| 0.0069 \| 2.5321 \| -48.6719 \| 0.9900 \| 51.2040 \| -160.5385 \| -27.4149 \| -1.3535 \| -1.3136 \| \| 0.0173 \| 3.3333 \| 250 \| 0.0069 \| 2.5321 \| -48.6719 \| 0.9900 \| 51.2040 \| -160.5385 \| -27.4149 \| -1.3535 \| -1.3136 \| \| 0.0347 \| 4.0 \| 300 \| 0.0069 \| 2.5321 \| -48.6719 \| 0.9900 \| 51.2040 \| -160.5385 \| -27.4149 \| -1.3535 \| -1.3136 \| \| 0.0173 \| 4.6667 \| 350 \| 0.0069 \| 2.5321 \| -48.6719 \| 0.9900 \| 51.2040 \| -160.5385 \| -27.4149 \| -1.3535 \| -1.3136 \| \| 0.0173 \| 5.3333 \| 400 \| 0.0069 \| 2.5321 \| -48.6719 \| 0.9900 \| 51.2040 \| -160.5385 \| -27.4148 \| -1.3535 \| -1.3136 \| \| 0.0173 \| 6.0 \| 450 \| 0.0069 \| 2.5321 \| -48.6719 \| 0.9900 \| 51.2040 \| -160.5385 \| -27.4148 \| -1.3535 \| -1.3136 \| \| 0.0347 \| 6.6667 \| 500 \| 0.0069 \| 2.5321 \| -48.6719 \| 0.9900 \| 51.2040 \| -160.5385 \| -27.4148 \| -1.3535 \| -1.3136 \| \| 0.0 \| 7.3333 \| 550 \| 0.0069 \| 2.5319 \| -48.6721 \| 0.9900 \| 51.2040 \| -160.5388 \| -27.4152 \| -1.3535 \| -1.3136 \| \| 0.0347 \| 8.0 \| 600 \| 0.0069 \| 2.5286 \| -48.6639 \| 0.9900 \| 51.1926 \| -160.5225 \| -27.4217 \| -1.3535 \| -1.3136 \| \| 0.0 \| 8.6667 \| 650 \| 0.0069 \| 2.5286 \| -48.6639 \| 0.9900 \| 51.1926 \| -160.5225 \| -27.4217 \| -1.3535 \| -1.3136 \| \| 0.0173 \| 9.3333 \| 700 \| 0.0069 \| 2.5286 \| -48.6639 \| 0.9900 \| 51.1926 \| -160.5225 \| -27.4217 \| -1.3535 \| -1.3136 \| \| 0.0 \| 10.0 \| 750 \| 0.0069 \| 2.5286 \| -48.6639 \| 0.9900 \| 51.1926 \| -160.5225 \| -27.4217 \| -1.3535 \| -1.3136 \| \| 0.0173 \| 10.6667 \| 800 \| 0.0069 \| 2.5286 \| -48.6639 \| 0.9900 \| 51.1926 \| -160.5225 \| -27.4217 \| -1.3535 \| -1.3136 \| \| 0.0 \| 11.3333 \| 850 \| 0.0069 \| 2.5286 \| -48.6639 \| 0.9900 \| 51.1926 \| -160.5225 \| -27.4217 \| -1.3535 \| -1.3136 \| \| 0.0 \| 12.0 \| 900 \| 0.0069 \| 2.5286 \| -48.6639 \| 0.9900 \| 51.1926 \| -160.5225 \| -27.4217 \| -1.3535 \| -1.3136 \| \| 0.0173 \| 12.6667 \| 950 \| 0.0069 \| 2.5286 \| -48.6639 \| 0.9900 \| 51.1926 \| -160.5225 \| -27.4217 \| -1.3535 \| -1.3136 \| \| 0.0 \| 13.3333 \| 1000 \| 0.0069 \| 2.5286 \| -48.6639 \| 0.9900 \| 51.1926 \| -160.5225 \| -27.4217 \| -1.3535 \| -1.3136 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1
HenryLau1103/uuu_fine_tune_taipower	HenryLau1103	2024-06-05T03:14:46Z	144	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-05T03:00:35Z	--- license: apache-2.0 ---
gaminwu/uuu_fine_tune_gpt2	gaminwu	2024-06-05T03:12:14Z	0	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-05T03:12:13Z	--- license: apache-2.0 ---
PhillipGuo/hp-lat-llama-PCA-epsilon0.5-pgd_layer8_16-def_layer8-wikitext-24	PhillipGuo	2024-06-05T03:12:00Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:11:47Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
NoteEB/custom-resnet18-model-EB	NoteEB	2024-06-05T03:03:12Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:59:12Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
leon625/TEST	leon625	2024-06-05T03:02:41Z	0	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-05T03:02:41Z	--- license: apache-2.0 ---
yehii/uuu_fine_tune_gpt2	yehii	2024-06-05T03:01:54Z	0	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-05T03:01:54Z	--- license: apache-2.0 ---
cutedogspark/tcp2023	cutedogspark	2024-06-05T03:01:48Z	0	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-05T03:01:48Z	--- license: apache-2.0 ---
Orion-zhen/Llama3-Chinese-Chat-emoji	Orion-zhen	2024-06-05T03:01:45Z	7	1	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "en", "zh", "dataset:shareAI/DPO-zh-en-emoji", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-06-03T08:34:35Z	--- license: llama3 datasets: - shareAI/DPO-zh-en-emoji language: - en - zh --- # Llama3-Chinese-Chat-emoji 在原模型shenzhi-wang/Llama3-70B-Chinese-Chat的基础上使用shareAI/DPO-zh-en-emoji进行QLoRA微调而来, 希望能重现原版llama3喜欢小表情的习惯失败惹, 原模型emoji能力已经被抑制惹, DPO也调不出来惹(悲) 新模型指路[Orion-zhen/Llama3-70B-Orion-Chinese](https://huggingface.co/Orion-zhen/Llama3-70B-Orion-Chinese)👈
DuridMing/tcp2024	DuridMing	2024-06-05T03:01:23Z	0	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-05T03:01:23Z	--- license: apache-2.0 ---
superdavidyeh/tcp2023	superdavidyeh	2024-06-05T03:01:11Z	0	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-05T03:01:11Z	--- license: apache-2.0 ---
Thanantikan/thannanthi-custom-resnet18-model	Thanantikan	2024-06-05T03:01:09Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T03:01:02Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
RyanTsai0321/tcp2024	RyanTsai0321	2024-06-05T03:00:33Z	0	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-05T03:00:33Z	--- license: apache-2.0 ---
HenryLau1103/tcp2023	HenryLau1103	2024-06-05T03:00:24Z	0	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-05T03:00:24Z	--- license: apache-2.0 ---
ManasaV22/fine_tuned_10012023	ManasaV22	2024-06-05T02:59:22Z	184	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-06-05T02:58:57Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
billkintao/billkintao-resnet18-model	billkintao	2024-06-05T02:59:12Z	79	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:59:05Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
rodrigoamf/ppo-LunarLander-v2	rodrigoamf	2024-06-05T02:58:07Z	0	0	stable-baselines3	[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]	reinforcement-learning	2024-06-05T01:05:01Z	--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 246.24 +/- 20.77 name: mean_reward verified: false --- # PPO Agent playing LunarLander-v2 This is a trained model of a PPO agent playing LunarLander-v2 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
billkintao/custom-resnet18-model	billkintao	2024-06-05T02:58:04Z	80	0	transformers	[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]	null	2024-06-05T02:57:52Z	--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]
LSHS/LSHS-Counselor-Bot	LSHS	2024-06-05T02:56:26Z	0	0	null	[ "document-question-answering", "arxiv:1910.09700", "license:afl-3.0", "region:us" ]	document-question-answering	2024-06-05T02:53:21Z	--- license: afl-3.0 pipeline_tag: document-question-answering --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

Vellimani/Mistral-7B-Instruct-v0.2-finetuned-QA

Vellimani

2024-06-05T05:43:37Z

8

0

transformers

[ "transformers", "safetensors", "mistral", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-04T08:15:43Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

tyzhu/squad_qa_title_v5_full_recite_full_passage_meta-llama_Llama-2-7b-hf_1e-4_lora

tyzhu

2024-06-05T05:40:11Z

0

null

[ "generated_from_trainer", "base_model:meta-llama/Llama-2-7b-hf", "base_model:finetune:meta-llama/Llama-2-7b-hf", "license:llama2", "region:us" ]

null

2024-06-05T01:47:22Z

--- license: llama2 base_model: meta-llama/Llama-2-7b-hf tags: - generated_from_trainer metrics: - accuracy model-index: - name: squad_qa_title_v5_full_recite_full_passage_meta-llama_Llama-2-7b-hf_1e-4_lora results: [] ---  # squad_qa_title_v5_full_recite_full_passage_meta-llama_Llama-2-7b-hf_1e-4_lora This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3478 - Accuracy: 0.8669 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 1 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - total_eval_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 50.0 ### Training results | Training Loss | Epoch | Step | Accuracy | Validation Loss | |:-------------:|:-----:|:----:|:--------:|:---------------:| | 1.2097 | 1.0 | 158 | 0.8026 | 0.6959 | | 0.2421 | 2.0 | 317 | 0.8546 | 0.2840 | | 0.1304 | 3.0 | 475 | 0.8658 | 0.2053 | | 0.1007 | 4.0 | 634 | 0.8667 | 0.2005 | | 0.0941 | 5.0 | 792 | 0.8665 | 0.2082 | | 0.0838 | 6.0 | 951 | 0.8669 | 0.2144 | | 0.0745 | 7.0 | 1109 | 0.8673 | 0.2232 | | 0.0667 | 8.0 | 1268 | 0.8667 | 0.2343 | | 0.0602 | 9.0 | 1426 | 0.8664 | 0.2490 | | 0.0558 | 10.0 | 1585 | 0.8659 | 0.2618 | | 0.0519 | 11.0 | 1743 | 0.8674 | 0.2661 | | 0.05 | 12.0 | 1902 | 0.8680 | 0.2679 | | 0.0475 | 13.0 | 2060 | 0.8664 | 0.2857 | | 0.0484 | 14.0 | 2219 | 0.8660 | 0.2898 | | 0.0466 | 15.0 | 2377 | 0.8664 | 0.2856 | | 0.0464 | 16.0 | 2536 | 0.8661 | 0.3037 | | 0.045 | 17.0 | 2694 | 0.8660 | 0.2976 | | 0.0459 | 18.0 | 2853 | 0.8660 | 0.2930 | | 0.0478 | 19.0 | 3011 | 0.8664 | 0.2994 | | 0.0444 | 20.0 | 3170 | 0.8665 | 0.3027 | | 0.0443 | 21.0 | 3328 | 0.8662 | 0.2945 | | 0.0432 | 22.0 | 3487 | 0.8665 | 0.3020 | | 0.0427 | 23.0 | 3645 | 0.8664 | 0.3122 | | 0.0436 | 24.0 | 3804 | 0.8663 | 0.3181 | | 0.0424 | 25.0 | 3962 | 0.8661 | 0.3300 | | 0.0442 | 26.0 | 4121 | 0.8662 | 0.3173 | | 0.0455 | 27.0 | 4279 | 0.8659 | 0.2914 | | 0.0464 | 28.0 | 4438 | 0.8663 | 0.3043 | | 0.0446 | 29.0 | 4596 | 0.8664 | 0.3201 | | 0.0427 | 30.0 | 4755 | 0.8666 | 0.3103 | | 0.0428 | 31.0 | 4913 | 0.8668 | 0.3120 | | 0.0422 | 32.0 | 5072 | 0.8665 | 0.3209 | | 0.0422 | 33.0 | 5230 | 0.8664 | 0.3256 | | 0.0426 | 34.0 | 5389 | 0.8665 | 0.3295 | | 0.0423 | 35.0 | 5547 | 0.8667 | 0.3375 | | 0.0421 | 36.0 | 5706 | 0.8666 | 0.3299 | | 0.0416 | 37.0 | 5864 | 0.8664 | 0.3438 | | 0.0429 | 38.0 | 6023 | 0.8657 | 0.3313 | | 0.0455 | 39.0 | 6181 | 0.8661 | 0.3100 | | 0.0433 | 40.0 | 6340 | 0.8663 | 0.3111 | | 0.0435 | 41.0 | 6498 | 0.8666 | 0.3134 | | 0.042 | 42.0 | 6657 | 0.8667 | 0.3188 | | 0.042 | 43.0 | 6815 | 0.8668 | 0.3219 | | 0.0413 | 44.0 | 6974 | 0.8666 | 0.3348 | | 0.0416 | 45.0 | 7110 | 0.3498 | 0.8666 | | 0.0413 | 46.0 | 7269 | 0.3380 | 0.8666 | | 0.0418 | 47.0 | 7427 | 0.3580 | 0.8668 | | 0.041 | 48.0 | 7586 | 0.3516 | 0.8667 | | 0.0411 | 49.0 | 7744 | 0.3468 | 0.8669 | | 0.0417 | 49.98 | 7900 | 0.3478 | 0.8669 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.14.1

LarryAIDraw/taoqi

LarryAIDraw

2024-06-05T05:35:09Z

0

null

[ "license:creativeml-openrail-m", "region:us" ]

null

2024-06-05T05:30:29Z

--- license: creativeml-openrail-m --- https://civitai.com/models/495578/taoqi-or-wuthering-waves

LarryAIDraw/genshin_v4

LarryAIDraw

2024-06-05T05:34:59Z

0

null

[ "license:creativeml-openrail-m", "region:us" ]

null

2024-06-05T05:30:04Z

--- license: creativeml-openrail-m --- https://civitai.com/models/357976/ponyall-characters-genshin-impact-124-characters-124

llama-duo/gemma2b-summarize-claude3sonnet-16k

llama-duo

2024-06-05T05:31:32Z

2

0

peft

[ "peft", "tensorboard", "safetensors", "gemma", "alignment-handbook", "trl", "sft", "generated_from_trainer", "dataset:llama-duo/synth_summarize_dataset_dedup", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "license:gemma", "4-bit", "bitsandbytes", "region:us" ]

null

2024-06-05T05:02:09Z

--- license: gemma library_name: peft tags: - alignment-handbook - trl - sft - generated_from_trainer base_model: google/gemma-2b datasets: - llama-duo/synth_summarize_dataset_dedup model-index: - name: gemma2b-summarize-claude3sonnet-16k results: [] ---  # gemma2b-summarize-claude3sonnet-16k This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.5454 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 3 - gradient_accumulation_steps: 2 - total_train_batch_size: 48 - total_eval_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.4889 | 1.0 | 51 | 2.5875 | | 1.1695 | 2.0 | 102 | 2.5044 | | 1.1003 | 3.0 | 153 | 2.5000 | | 1.0537 | 4.0 | 204 | 2.5040 | | 1.0131 | 5.0 | 255 | 2.5131 | | 0.995 | 6.0 | 306 | 2.5208 | | 0.9739 | 7.0 | 357 | 2.5337 | | 0.9626 | 8.0 | 408 | 2.5445 | | 0.9572 | 9.0 | 459 | 2.5443 | | 0.9554 | 10.0 | 510 | 2.5454 | ### Framework versions - PEFT 0.10.0 - Transformers 4.40.0 - Pytorch 2.2.2+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1

zyylol/ppo-LunarLander-v2

zyylol

2024-06-05T05:30:09Z

0

stable-baselines3

[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]

reinforcement-learning

2024-06-04T07:10:57Z

--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 272.60 +/- 16.14 name: mean_reward verified: false --- # **PPO** Agent playing **LunarLander-v2** This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```

imlixinyang/director3d

imlixinyang

2024-06-05T05:29:44Z

0

null

[ "license:cc-by-nc-nd-4.0", "region:us" ]

null

2024-06-05T05:12:18Z

--- license: cc-by-nc-nd-4.0 ---

tsavage68/UTI_L3_1000steps_1e6rate_05beta_CSFTDPO

tsavage68

2024-06-05T05:28:47Z

6

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T05:24:46Z

--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e6rate_05beta_CSFTDPO results: [] ---  # UTI_L3_1000steps_1e6rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0078 - Rewards/chosen: 2.5926 - Rewards/rejected: -13.7164 - Rewards/accuracies: 0.9900 - Rewards/margins: 16.3089 - Logps/rejected: -90.6274 - Logps/chosen: -27.2939 - Logits/rejected: -1.3641 - Logits/chosen: -1.3371 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-06 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.5483 | 0.3333 | 25 | 0.2812 | 0.2629 | -1.0915 | 0.9900 | 1.3544 | -65.3776 | -31.9532 | -1.3242 | -1.3091 | | 0.0186 | 0.6667 | 50 | 0.0204 | 1.4814 | -6.2620 | 0.9900 | 7.7434 | -75.7187 | -29.5163 | -1.3323 | -1.3150 | | 0.0007 | 1.0 | 75 | 0.0124 | 2.1023 | -8.8403 | 0.9900 | 10.9426 | -80.8753 | -28.2744 | -1.3425 | -1.3227 | | 0.0174 | 1.3333 | 100 | 0.0110 | 2.7866 | -9.0480 | 0.9900 | 11.8346 | -81.2906 | -26.9057 | -1.3476 | -1.3272 | | 0.0173 | 1.6667 | 125 | 0.0107 | 2.2710 | -10.8326 | 0.9900 | 13.1036 | -84.8600 | -27.9370 | -1.3498 | -1.3269 | | 0.0348 | 2.0 | 150 | 0.0079 | 2.5738 | -13.4526 | 0.9900 | 16.0264 | -90.0999 | -27.3315 | -1.3620 | -1.3349 | | 0.0 | 2.3333 | 175 | 0.0079 | 2.5665 | -13.4456 | 0.9900 | 16.0121 | -90.0858 | -27.3459 | -1.3620 | -1.3348 | | 0.0 | 2.6667 | 200 | 0.0078 | 2.5714 | -13.4484 | 0.9900 | 16.0198 | -90.0914 | -27.3362 | -1.3619 | -1.3348 | | 0.0 | 3.0 | 225 | 0.0079 | 2.5744 | -13.4805 | 0.9900 | 16.0549 | -90.1557 | -27.3302 | -1.3623 | -1.3352 | | 0.0173 | 3.3333 | 250 | 0.0078 | 2.5790 | -13.4989 | 0.9900 | 16.0779 | -90.1926 | -27.3210 | -1.3623 | -1.3352 | | 0.0173 | 3.6667 | 275 | 0.0077 | 2.5749 | -13.5072 | 0.9900 | 16.0821 | -90.2091 | -27.3291 | -1.3623 | -1.3351 | | 0.0347 | 4.0 | 300 | 0.0078 | 2.5828 | -13.5202 | 0.9900 | 16.1030 | -90.2351 | -27.3134 | -1.3626 | -1.3355 | | 0.0 | 4.3333 | 325 | 0.0077 | 2.5858 | -13.5544 | 0.9900 | 16.1403 | -90.3036 | -27.3074 | -1.3626 | -1.3355 | | 0.0173 | 4.6667 | 350 | 0.0078 | 2.5816 | -13.5650 | 0.9900 | 16.1466 | -90.3246 | -27.3158 | -1.3628 | -1.3357 | | 0.0347 | 5.0 | 375 | 0.0079 | 2.5779 | -13.5622 | 0.9900 | 16.1400 | -90.3190 | -27.3233 | -1.3628 | -1.3356 | | 0.0173 | 5.3333 | 400 | 0.0077 | 2.5852 | -13.5789 | 0.9900 | 16.1641 | -90.3526 | -27.3087 | -1.3630 | -1.3358 | | 0.0347 | 5.6667 | 425 | 0.0078 | 2.5848 | -13.6053 | 0.9900 | 16.1901 | -90.4053 | -27.3094 | -1.3632 | -1.3361 | | 0.0173 | 6.0 | 450 | 0.0077 | 2.5855 | -13.6105 | 0.9900 | 16.1960 | -90.4156 | -27.3079 | -1.3634 | -1.3364 | | 0.0 | 6.3333 | 475 | 0.0079 | 2.5850 | -13.6238 | 0.9900 | 16.2087 | -90.4422 | -27.3091 | -1.3635 | -1.3364 | | 0.0347 | 6.6667 | 500 | 0.0077 | 2.5926 | -13.6436 | 0.9900 | 16.2362 | -90.4819 | -27.2938 | -1.3635 | -1.3364 | | 0.0 | 7.0 | 525 | 0.0077 | 2.5890 | -13.6520 | 0.9900 | 16.2410 | -90.4987 | -27.3010 | -1.3635 | -1.3364 | | 0.0 | 7.3333 | 550 | 0.0077 | 2.5868 | -13.6463 | 0.9900 | 16.2331 | -90.4873 | -27.3054 | -1.3636 | -1.3365 | | 0.0173 | 7.6667 | 575 | 0.0077 | 2.5918 | -13.6721 | 0.9900 | 16.2639 | -90.5389 | -27.2955 | -1.3637 | -1.3366 | | 0.0347 | 8.0 | 600 | 0.0078 | 2.5868 | -13.6787 | 0.9900 | 16.2654 | -90.5520 | -27.3055 | -1.3638 | -1.3367 | | 0.0347 | 8.3333 | 625 | 0.0077 | 2.5930 | -13.6789 | 0.9900 | 16.2719 | -90.5525 | -27.2931 | -1.3639 | -1.3368 | | 0.0 | 8.6667 | 650 | 0.0078 | 2.5892 | -13.6871 | 0.9900 | 16.2763 | -90.5689 | -27.3006 | -1.3638 | -1.3367 | | 0.0 | 9.0 | 675 | 0.0077 | 2.5903 | -13.6943 | 0.9900 | 16.2847 | -90.5834 | -27.2984 | -1.3639 | -1.3368 | | 0.0173 | 9.3333 | 700 | 0.0078 | 2.5860 | -13.7028 | 0.9900 | 16.2888 | -90.6002 | -27.3070 | -1.3642 | -1.3371 | | 0.0173 | 9.6667 | 725 | 0.0077 | 2.5865 | -13.6964 | 0.9900 | 16.2830 | -90.5876 | -27.3060 | -1.3641 | -1.3370 | | 0.0 | 10.0 | 750 | 0.0077 | 2.5939 | -13.7066 | 0.9900 | 16.3006 | -90.6079 | -27.2912 | -1.3641 | -1.3370 | | 0.0 | 10.3333 | 775 | 0.0079 | 2.5928 | -13.7020 | 0.9900 | 16.2947 | -90.5986 | -27.2935 | -1.3640 | -1.3369 | | 0.0173 | 10.6667 | 800 | 0.0078 | 2.5909 | -13.7013 | 0.9900 | 16.2922 | -90.5973 | -27.2972 | -1.3642 | -1.3371 | | 0.0173 | 11.0 | 825 | 0.0076 | 2.5913 | -13.7123 | 0.9900 | 16.3036 | -90.6193 | -27.2965 | -1.3641 | -1.3370 | | 0.0 | 11.3333 | 850 | 0.0077 | 2.5908 | -13.7072 | 0.9900 | 16.2980 | -90.6090 | -27.2974 | -1.3642 | -1.3371 | | 0.0347 | 11.6667 | 875 | 0.0078 | 2.5953 | -13.7055 | 0.9900 | 16.3008 | -90.6056 | -27.2884 | -1.3640 | -1.3369 | | 0.0 | 12.0 | 900 | 0.0078 | 2.5866 | -13.7139 | 0.9900 | 16.3005 | -90.6224 | -27.3058 | -1.3642 | -1.3370 | | 0.0173 | 12.3333 | 925 | 0.0077 | 2.5953 | -13.6932 | 0.9900 | 16.2885 | -90.5811 | -27.2884 | -1.3640 | -1.3369 | | 0.0173 | 12.6667 | 950 | 0.0077 | 2.5928 | -13.7129 | 0.9900 | 16.3057 | -90.6204 | -27.2934 | -1.3641 | -1.3370 | | 0.0347 | 13.0 | 975 | 0.0078 | 2.5926 | -13.7164 | 0.9900 | 16.3089 | -90.6274 | -27.2939 | -1.3641 | -1.3371 | | 0.0 | 13.3333 | 1000 | 0.0078 | 2.5926 | -13.7164 | 0.9900 | 16.3089 | -90.6274 | -27.2939 | -1.3641 | -1.3371 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1

nuttcutee/Custom_tiger_google_vit-base-patch16-224

nuttcutee

2024-06-05T05:14:10Z

219

0

transformers

[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

2024-06-05T05:13:51Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

llama-duo/gemma2b-summarize-gemini1_5flash-16k

llama-duo

2024-06-05T05:05:24Z

2

0

peft

[ "peft", "tensorboard", "safetensors", "gemma", "alignment-handbook", "trl", "sft", "generated_from_trainer", "dataset:llama-duo/synth_summarize_dataset_dedup", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "license:gemma", "4-bit", "bitsandbytes", "region:us" ]

null

2024-06-05T04:50:07Z

--- license: gemma library_name: peft tags: - alignment-handbook - trl - sft - generated_from_trainer base_model: google/gemma-2b datasets: - llama-duo/synth_summarize_dataset_dedup model-index: - name: gemma2b-summarize-gemini1_5flash-16k results: [] ---  # gemma2b-summarize-gemini1_5flash-16k This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.5319 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.0246 | 0.9811 | 26 | 2.6613 | | 1.3202 | 2.0 | 53 | 2.5405 | | 1.1694 | 2.9811 | 79 | 2.5125 | | 1.1076 | 4.0 | 106 | 2.5138 | | 1.0651 | 4.9811 | 132 | 2.5086 | | 1.0394 | 6.0 | 159 | 2.5248 | | 1.0232 | 6.9811 | 185 | 2.5264 | | 1.0042 | 8.0 | 212 | 2.5296 | | 1.0109 | 8.9811 | 238 | 2.5319 | | 1.0064 | 9.8113 | 260 | 2.5319 | ### Framework versions - PEFT 0.11.1 - Transformers 4.40.1 - Pytorch 2.2.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1

msubhasish28/my_awesome_model

msubhasish28

2024-06-05T04:49:49Z

105

0

transformers

[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-02-15T01:32:32Z

--- license: apache-2.0 base_model: distilbert/distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: my_awesome_model results: [] ---  # my_awesome_model This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2265 - Accuracy: 0.9326 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.2257 | 1.0 | 1563 | 0.1940 | 0.9259 | | 0.1446 | 2.0 | 3126 | 0.2265 | 0.9326 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.2.2 - Datasets 2.14.6 - Tokenizers 0.19.1

alpcansoydas/iban_ocr_large_18k_epoch5

alpcansoydas

2024-06-05T04:49:22Z

50

0

transformers

[ "transformers", "safetensors", "vision-encoder-decoder", "image-text-to-text", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

image-text-to-text

2024-06-05T01:14:43Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  [{'loss': 3.0878, 'learning_rate': 4.8630820399113085e-05, 'epoch': 0.14, 'step': 500}, {'loss': 1.9885, 'learning_rate': 4.7245011086474504e-05, 'epoch': 0.28, 'step': 1000}, {'loss': 1.7381, 'learning_rate': 4.585920177383592e-05, 'epoch': 0.42, 'step': 1500}, {'loss': 1.4517, 'learning_rate': 4.447339246119734e-05, 'epoch': 0.55, 'step': 2000}, {'loss': 1.225, 'learning_rate': 4.3087583148558755e-05, 'epoch': 0.69, 'step': 2500}, {'loss': 1.1094, 'learning_rate': 4.1704545454545456e-05, 'epoch': 0.83, 'step': 3000}, {'loss': 1.0243, 'learning_rate': 4.0318736141906875e-05, 'epoch': 0.97, 'step': 3500}, {'eval_loss': 0.9151868224143982, 'eval_cer': 0.1013281301966697, 'eval_runtime': 2841.3659, 'eval_samples_per_second': 1.27, 'eval_steps_per_second': 0.317, 'epoch': 1.0, 'step': 3608}, {'loss': 0.8896, 'learning_rate': 3.8932926829268294e-05, 'epoch': 1.11, 'step': 4000}, {'loss': 0.7499, 'learning_rate': 3.754711751662971e-05, 'epoch': 1.25, 'step': 4500}, {'loss': 0.7259, 'learning_rate': 3.616130820399113e-05, 'epoch': 1.39, 'step': 5000}, {'loss': 0.7324, 'learning_rate': 3.477549889135255e-05, 'epoch': 1.52, 'step': 5500}, {'loss': 0.6456, 'learning_rate': 3.338968957871397e-05, 'epoch': 1.66, 'step': 6000}, {'loss': 0.563, 'learning_rate': 3.200388026607539e-05, 'epoch': 1.8, 'step': 6500}, {'loss': 0.5532, 'learning_rate': 3.061807095343681e-05, 'epoch': 1.94, 'step': 7000}, {'eval_loss': 0.43645456433296204, 'eval_cer': 0.037061262499722844, 'eval_runtime': 2791.7981, 'eval_samples_per_second': 1.292, 'eval_steps_per_second': 0.323, 'epoch': 2.0, 'step': 7216}, {'loss': 0.4441, 'learning_rate': 2.9235033259423506e-05, 'epoch': 2.08, 'step': 7500}, {'loss': 0.4233, 'learning_rate': 2.7849223946784925e-05, 'epoch': 2.22, 'step': 8000}, {'loss': 0.3911, 'learning_rate': 2.646618625277162e-05, 'epoch': 2.36, 'step': 8500}, {'loss': 0.3454, 'learning_rate': 2.5080376940133038e-05, 'epoch': 2.49, 'step': 9000}, {'loss': 0.3201, 'learning_rate': 2.3694567627494457e-05, 'epoch': 2.63, 'step': 9500}, {'loss': 0.2908, 'learning_rate': 2.2308758314855876e-05, 'epoch': 2.77, 'step': 10000}, {'loss': 0.2651, 'learning_rate': 2.0922949002217295e-05, 'epoch': 2.91, 'step': 10500}, {'eval_loss': 0.26305779814720154, 'eval_cer': 0.021252300392452496, 'eval_runtime': 2821.9411, 'eval_samples_per_second': 1.279, 'eval_steps_per_second': 0.32, 'epoch': 3.0, 'step': 10824}, {'loss': 0.2313, 'learning_rate': 1.9537139689578714e-05, 'epoch': 3.05, 'step': 11000}, {'loss': 0.1767, 'learning_rate': 1.8151330376940133e-05, 'epoch': 3.19, 'step': 11500}, {'loss': 0.196, 'learning_rate': 1.6765521064301552e-05, 'epoch': 3.33, 'step': 12000}, {'loss': 0.1668, 'learning_rate': 1.537971175166297e-05, 'epoch': 3.46, 'step': 12500}, {'loss': 0.1489, 'learning_rate': 1.3993902439024392e-05, 'epoch': 3.6, 'step': 13000}, {'loss': 0.1439, 'learning_rate': 1.260809312638581e-05, 'epoch': 3.74, 'step': 13500}, {'loss': 0.1413, 'learning_rate': 1.122228381374723e-05, 'epoch': 3.88, 'step': 14000}, {'eval_loss': 0.17799262702465057, 'eval_cer': 0.011995299439036829, 'eval_runtime': 2814.9178, 'eval_samples_per_second': 1.282, 'eval_steps_per_second': 0.32, 'epoch': 4.0, 'step': 14432}, {'loss': 0.1193, 'learning_rate': 9.836474501108648e-06, 'epoch': 4.02, 'step': 14500}, {'loss': 0.0904, 'learning_rate': 8.453436807095343e-06, 'epoch': 4.16, 'step': 15000}, {'loss': 0.0822, 'learning_rate': 7.070399113082041e-06, 'epoch': 4.3, 'step': 15500}, {'loss': 0.0675, 'learning_rate': 5.684589800443459e-06, 'epoch': 4.43, 'step': 16000}, {'loss': 0.0606, 'learning_rate': 4.298780487804878e-06, 'epoch': 4.57, 'step': 16500}, {'loss': 0.055, 'learning_rate': 2.912971175166297e-06, 'epoch': 4.71, 'step': 17000}, {'loss': 0.0476, 'learning_rate': 1.5271618625277162e-06, 'epoch': 4.85, 'step': 17500}, {'loss': 0.0513, 'learning_rate': 1.4135254988913526e-07, 'epoch': 4.99, 'step': 18000}, {'eval_loss': 0.10952820628881454, 'eval_cer': 0.007350169619298907, 'eval_runtime': 2798.4707, 'eval_samples_per_second': 1.289, 'eval_steps_per_second': 0.322, 'epoch': 5.0, 'step': 18040}, {'train_runtime': 58940.2961, 'train_samples_per_second': 1.224, 'train_steps_per_second': 0.306, 'total_flos': 9.69366452586519e+19, 'train_loss': 0.575048929558625, 'epoch': 5.0, 'step': 18040}] ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

chainup244/Qwen-Qwen1.5-1.8B-1717562389

chainup244

2024-06-05T04:43:51Z

144

0

transformers

[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T04:39:53Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

Orion-zhen/Llama3-70B-Orion-Chinese-4bpw-exl2

Orion-zhen

2024-06-05T04:43:35Z

11

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "zh", "en", "license:mit", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "exl2", "region:us" ]

text-generation

2024-06-05T02:40:44Z

--- license: mit language: - zh - en --- # Llama3-70B-Orion-Chinese-4bpw-exl2 这是对[Orion-zhen/Llama3-70B-Orion-Chinese](https://huggingface.co/Orion-zhen/Llama3-70B-Orion-Chinese)的exl2 4bpw量化版采用[Orion-zhen/firefly-exl-calibration](https://huggingface.co/datasets/Orion-zhen/firefly-exl-calibration)作为校准数据集, 以获得较少的中文性能损失并降低出现乱码的概率

hdve/google-gemma-7b-1717562322

hdve

2024-06-05T04:41:22Z

8

0

transformers

[ "transformers", "safetensors", "gemma", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T04:38:45Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

llama-duo/gemma2b-summarize-gpt4o-1k

llama-duo

2024-06-05T04:40:09Z

1

0

peft

[ "peft", "tensorboard", "safetensors", "gemma", "alignment-handbook", "trl", "sft", "generated_from_trainer", "dataset:llama-duo/synth_summarize_dataset_dedup", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "license:gemma", "4-bit", "bitsandbytes", "region:us" ]

null

2024-06-05T04:38:02Z

--- license: gemma library_name: peft tags: - alignment-handbook - trl - sft - generated_from_trainer base_model: google/gemma-2b datasets: - llama-duo/synth_summarize_dataset_dedup model-index: - name: gemma2b-summarize-gpt4o-1k results: [] ---  # gemma2b-summarize-gpt4o-1k This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.7415 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 3 - gradient_accumulation_steps: 2 - total_train_batch_size: 48 - total_eval_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 2.9975 | 0.8 | 2 | 3.1990 | | 2.8744 | 2.0 | 5 | 3.0048 | | 2.8744 | 2.8 | 7 | 2.8992 | | 2.3833 | 4.0 | 10 | 2.8237 | | 2.3833 | 4.8 | 12 | 2.7889 | | 2.1436 | 6.0 | 15 | 2.7588 | | 2.1436 | 6.8 | 17 | 2.7501 | | 2.0522 | 8.0 | 20 | 2.7415 | ### Framework versions - PEFT 0.11.1 - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1

Jongruk/Custom_tiger_google_vit-base-patch16-224

Jongruk

2024-06-05T04:34:18Z

198

0

transformers

[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

2024-06-05T04:33:50Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

netcat420/MFANN3bv0.12

netcat420

2024-06-05T04:34:12Z

9

0

transformers

[ "transformers", "safetensors", "phi", "text-generation", "en", "dataset:netcat420/MFANN", "arxiv:1910.09700", "license:mit", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T04:00:14Z

--- library_name: transformers license: mit datasets: - netcat420/MFANN language: - en pipeline_tag: text-generation --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

llama-duo/gemma2b-summarize-gemini1_5flash-1k

llama-duo

2024-06-05T04:32:17Z

1

0

peft

[ "peft", "tensorboard", "safetensors", "gemma", "alignment-handbook", "trl", "sft", "generated_from_trainer", "dataset:llama-duo/synth_summarize_dataset_dedup", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "license:gemma", "4-bit", "bitsandbytes", "region:us" ]

null

2024-06-05T04:30:53Z

--- license: gemma library_name: peft tags: - alignment-handbook - trl - sft - generated_from_trainer base_model: google/gemma-2b datasets: - llama-duo/synth_summarize_dataset_dedup model-index: - name: gemma2b-summarize-gemini1_5flash-1k results: [] ---  # gemma2b-summarize-gemini1_5flash-1k This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.7426 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 2.9957 | 1.0 | 2 | 3.1984 | | 2.9957 | 2.0 | 4 | 3.0673 | | 2.8525 | 3.0 | 6 | 2.9478 | | 2.8525 | 4.0 | 8 | 2.8806 | | 2.3323 | 5.0 | 10 | 2.8382 | | 2.3323 | 6.0 | 12 | 2.8050 | | 2.3323 | 7.0 | 14 | 2.7636 | | 2.0887 | 8.0 | 16 | 2.7495 | | 2.0887 | 9.0 | 18 | 2.7433 | | 1.9997 | 10.0 | 20 | 2.7426 | ### Framework versions - PEFT 0.11.1 - Transformers 4.40.1 - Pytorch 2.2.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1

warwavn/Custom_tiger_google_vit-base-patch16-224

warwavn

2024-06-05T04:31:14Z

196

0

transformers

[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

2024-06-05T04:30:56Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

duyntnet/bagel-8b-v1.0-imatrix-GGUF

duyntnet

2024-06-05T04:30:48Z

44

0

transformers

[ "transformers", "gguf", "imatrix", "bagel-8b-v1.0", "text-generation", "en", "license:other", "region:us", "conversational" ]

text-generation

2024-06-05T02:10:12Z

--- license: other language: - en pipeline_tag: text-generation inference: false tags: - transformers - gguf - imatrix - bagel-8b-v1.0 --- Quantizations of https://huggingface.co/jondurbin/bagel-8b-v1.0 # From original readme ## Prompt formatting This model uses the llama-3-instruct prompt template, and is provided in the tokenizer config. You can use the `apply_chat_template` method to accurate format prompts, e.g.: ```python import transformers tokenizer = transformers.AutoTokenizer.from_pretrained("jondurbin/bagel-8b-v1.0", trust_remote_code=True) chat = [ {"role": "system", "content": "You are Bob, a friendly AI assistant."}, {"role": "user", "content": "Hello, how are you?"}, {"role": "assistant", "content": "I'm doing great. How can I help you today?"}, {"role": "user", "content": "I'd like to show off how chat templating works!"}, ] print(tokenizer.apply_chat_template(chat, tokenize=False)) ```

Chanchaiw/Custom_tiger_google_vit-base-patch16-224

Chanchaiw

2024-06-05T04:30:45Z

222

0

transformers

[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

2024-06-05T04:30:27Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

panit/Custom_tiger_google_vit-base-patch16-224

panit

2024-06-05T04:30:33Z

196

0

transformers

[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

2024-06-05T04:30:04Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

pankajchouhan07/AccojuntData

pankajchouhan07

2024-06-05T04:30:08Z

0

1

null

[ "license:apache-2.0", "region:us" ]

null

2024-06-05T04:30:08Z

--- license: apache-2.0 ---

ymoslem/whisper-small-ga2en-v5.5-r

ymoslem

2024-06-05T04:29:53Z

19

1

transformers

[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "generated_from_trainer", "ga", "en", "dataset:ymoslem/IWSLT2023-GA-EN", "dataset:ymoslem/FLEURS-GA-EN", "dataset:ymoslem/BitesizeIrish-GA-EN", "dataset:ymoslem/SpokenWords-GA-EN-MTed", "dataset:ymoslem/Tatoeba-Speech-Irish", "dataset:ymoslem/Wikimedia-Speech-Irish", "base_model:openai/whisper-small", "base_model:finetune:openai/whisper-small", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2024-06-04T20:37:43Z

--- language: - ga - en license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - ymoslem/IWSLT2023-GA-EN - ymoslem/FLEURS-GA-EN - ymoslem/BitesizeIrish-GA-EN - ymoslem/SpokenWords-GA-EN-MTed - ymoslem/Tatoeba-Speech-Irish - ymoslem/Wikimedia-Speech-Irish metrics: - bleu - wer model-index: - name: Whisper Small GA-EN Speech Translation results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia type: ymoslem/IWSLT2023-GA-EN metrics: - name: Bleu type: bleu value: 32.44 - name: Wer type: wer value: 63.259792886087354 ---  # Whisper Small GA-EN Speech Translation This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia dataset. It achieves the following results on the evaluation set: - Loss: 1.3690 - Bleu: 32.44 - Chrf: 48.06 - Wer: 63.2598 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.01 - training_steps: 3000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Wer | |:-------------:|:------:|:----:|:---------------:|:-----:|:-----:|:--------:| | 2.3655 | 0.0438 | 100 | 1.7709 | 8.84 | 26.21 | 127.7803 | | 1.8998 | 0.0876 | 200 | 1.5198 | 14.9 | 32.89 | 99.2796 | | 1.5421 | 0.1313 | 300 | 1.3972 | 16.15 | 35.77 | 86.8077 | | 1.3154 | 0.1751 | 400 | 1.3412 | 20.46 | 39.48 | 83.0707 | | 1.1138 | 0.2189 | 500 | 1.3126 | 23.16 | 41.28 | 74.1108 | | 0.9814 | 0.2627 | 600 | 1.3217 | 25.56 | 41.67 | 68.7528 | | 0.8897 | 0.3065 | 700 | 1.2859 | 27.0 | 43.54 | 66.3215 | | 0.7495 | 0.3503 | 800 | 1.2668 | 21.71 | 43.03 | 75.7767 | | 0.7068 | 0.3940 | 900 | 1.2852 | 17.86 | 40.88 | 106.0333 | | 0.6002 | 0.4378 | 1000 | 1.2476 | 24.0 | 44.26 | 78.4331 | | 0.4989 | 0.4816 | 1100 | 1.2756 | 28.88 | 45.57 | 67.2670 | | 0.4464 | 0.5254 | 1200 | 1.2756 | 27.81 | 45.53 | 66.8618 | | 0.3883 | 0.5692 | 1300 | 1.2799 | 29.84 | 46.03 | 64.0702 | | 0.341 | 0.6130 | 1400 | 1.2693 | 26.51 | 43.97 | 75.3715 | | 0.2853 | 0.6567 | 1500 | 1.3310 | 26.99 | 45.58 | 74.0207 | | 0.2611 | 0.7005 | 1600 | 1.3022 | 25.83 | 44.79 | 73.4354 | | 0.2013 | 0.7443 | 1700 | 1.3266 | 30.78 | 46.61 | 63.6650 | | 0.1886 | 0.7881 | 1800 | 1.2943 | 25.56 | 45.46 | 73.7055 | | 0.1517 | 0.8319 | 1900 | 1.3193 | 28.93 | 45.09 | 64.3854 | | 0.1288 | 0.8757 | 2000 | 1.3567 | 28.22 | 44.75 | 67.6722 | | 0.1129 | 0.9194 | 2100 | 1.3431 | 29.55 | 46.22 | 66.2314 | | 0.1 | 0.9632 | 2200 | 1.3365 | 31.46 | 48.14 | 64.9257 | | 0.0505 | 1.0070 | 2300 | 1.3557 | 30.37 | 47.16 | 64.1153 | | 0.0468 | 1.0508 | 2400 | 1.3648 | 31.57 | 48.17 | 62.0891 | | 0.0373 | 1.0946 | 2500 | 1.3661 | 31.56 | 47.76 | 64.7456 | | 0.0297 | 1.1384 | 2600 | 1.3638 | 31.13 | 47.74 | 64.3854 | | 0.0283 | 1.1821 | 2700 | 1.3847 | 29.98 | 47.54 | 65.9613 | | 0.0302 | 1.2259 | 2800 | 1.3730 | 32.32 | 48.28 | 64.0252 | | 0.0229 | 1.2697 | 2900 | 1.3702 | 31.47 | 47.55 | 65.1508 | | 0.0262 | 1.3135 | 3000 | 1.3690 | 32.44 | 48.06 | 63.2598 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.2.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1

AgentBG/Custom_tiger_google_vit-base-patch16-224

AgentBG

2024-06-05T04:27:10Z

222

0

transformers

[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

2024-06-05T04:26:40Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

tsavage68/UTI_L3_1000steps_1e7rate_05beta_CSFTDPO

tsavage68

2024-06-05T04:25:35Z

6

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T04:21:20Z

--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e7rate_05beta_CSFTDPO results: [] ---  # UTI_L3_1000steps_1e7rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0164 - Rewards/chosen: 1.6699 - Rewards/rejected: -6.1458 - Rewards/accuracies: 0.9900 - Rewards/margins: 7.8157 - Logps/rejected: -75.4864 - Logps/chosen: -29.1393 - Logits/rejected: -1.3321 - Logits/chosen: -1.3145 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-07 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6936 | 0.3333 | 25 | 0.6887 | -0.0007 | -0.0109 | 0.5300 | 0.0102 | -63.2166 | -32.4804 | -1.3231 | -1.3079 | | 0.6544 | 0.6667 | 50 | 0.6317 | 0.0212 | -0.1104 | 0.8500 | 0.1316 | -63.4155 | -32.4367 | -1.3229 | -1.3078 | | 0.5537 | 1.0 | 75 | 0.5050 | 0.0832 | -0.3693 | 0.9400 | 0.4525 | -63.9333 | -32.3125 | -1.3234 | -1.3083 | | 0.3404 | 1.3333 | 100 | 0.3397 | 0.1907 | -0.8797 | 0.9800 | 1.0704 | -64.9540 | -32.0976 | -1.3239 | -1.3089 | | 0.2191 | 1.6667 | 125 | 0.2217 | 0.3556 | -1.4579 | 0.9900 | 1.8135 | -66.1104 | -31.7678 | -1.3246 | -1.3095 | | 0.1721 | 2.0 | 150 | 0.1545 | 0.5057 | -1.8983 | 0.9900 | 2.4040 | -66.9912 | -31.4675 | -1.3248 | -1.3097 | | 0.0763 | 2.3333 | 175 | 0.1116 | 0.6367 | -2.3670 | 0.9900 | 3.0037 | -67.9287 | -31.2056 | -1.3255 | -1.3103 | | 0.0669 | 2.6667 | 200 | 0.0818 | 0.7555 | -2.7499 | 0.9900 | 3.5054 | -68.6945 | -30.9681 | -1.3264 | -1.3111 | | 0.0388 | 3.0 | 225 | 0.0620 | 0.8673 | -3.2396 | 0.9900 | 4.1068 | -69.6738 | -30.7445 | -1.3267 | -1.3113 | | 0.0653 | 3.3333 | 250 | 0.0506 | 0.9617 | -3.6047 | 0.9900 | 4.5664 | -70.4041 | -30.5557 | -1.3274 | -1.3119 | | 0.0332 | 3.6667 | 275 | 0.0406 | 1.0595 | -4.0208 | 0.9900 | 5.0803 | -71.2363 | -30.3600 | -1.3276 | -1.3119 | | 0.0522 | 4.0 | 300 | 0.0339 | 1.1423 | -4.3687 | 0.9900 | 5.5110 | -71.9320 | -30.1943 | -1.3282 | -1.3123 | | 0.005 | 4.3333 | 325 | 0.0293 | 1.2385 | -4.6734 | 0.9900 | 5.9119 | -72.5414 | -30.0020 | -1.3286 | -1.3124 | | 0.0284 | 4.6667 | 350 | 0.0256 | 1.3119 | -4.9072 | 0.9900 | 6.2191 | -73.0091 | -29.8553 | -1.3295 | -1.3132 | | 0.0393 | 5.0 | 375 | 0.0229 | 1.3864 | -5.1293 | 0.9900 | 6.5157 | -73.4534 | -29.7063 | -1.3298 | -1.3132 | | 0.0261 | 5.3333 | 400 | 0.0214 | 1.4513 | -5.3049 | 0.9900 | 6.7563 | -73.8046 | -29.5763 | -1.3302 | -1.3135 | | 0.0403 | 5.6667 | 425 | 0.0204 | 1.4964 | -5.4655 | 0.9900 | 6.9619 | -74.1256 | -29.4862 | -1.3304 | -1.3136 | | 0.0197 | 6.0 | 450 | 0.0190 | 1.5233 | -5.6170 | 0.9900 | 7.1404 | -74.4287 | -29.4324 | -1.3307 | -1.3137 | | 0.0023 | 6.3333 | 475 | 0.0186 | 1.5672 | -5.7288 | 0.9900 | 7.2960 | -74.6523 | -29.3447 | -1.3310 | -1.3139 | | 0.0391 | 6.6667 | 500 | 0.0181 | 1.5895 | -5.8057 | 0.9900 | 7.3952 | -74.8060 | -29.2999 | -1.3313 | -1.3141 | | 0.0044 | 7.0 | 525 | 0.0174 | 1.6125 | -5.9110 | 0.9900 | 7.5235 | -75.0167 | -29.2541 | -1.3314 | -1.3141 | | 0.0034 | 7.3333 | 550 | 0.0178 | 1.6265 | -5.9426 | 0.9900 | 7.5691 | -75.0799 | -29.2260 | -1.3316 | -1.3143 | | 0.0214 | 7.6667 | 575 | 0.0167 | 1.6348 | -6.0154 | 0.9900 | 7.6502 | -75.2254 | -29.2094 | -1.3316 | -1.3143 | | 0.0363 | 8.0 | 600 | 0.0166 | 1.6397 | -6.0402 | 0.9900 | 7.6798 | -75.2751 | -29.1997 | -1.3318 | -1.3144 | | 0.0366 | 8.3333 | 625 | 0.0168 | 1.6498 | -6.0578 | 0.9900 | 7.7076 | -75.3102 | -29.1794 | -1.3320 | -1.3145 | | 0.0011 | 8.6667 | 650 | 0.0168 | 1.6607 | -6.0845 | 0.9900 | 7.7452 | -75.3637 | -29.1576 | -1.3319 | -1.3145 | | 0.0043 | 9.0 | 675 | 0.0167 | 1.6659 | -6.1131 | 0.9900 | 7.7790 | -75.4209 | -29.1472 | -1.3321 | -1.3146 | | 0.0197 | 9.3333 | 700 | 0.0161 | 1.6703 | -6.1301 | 0.9900 | 7.8004 | -75.4550 | -29.1385 | -1.3320 | -1.3145 | | 0.0186 | 9.6667 | 725 | 0.0165 | 1.6713 | -6.1341 | 0.9900 | 7.8054 | -75.4628 | -29.1364 | -1.3321 | -1.3147 | | 0.0039 | 10.0 | 750 | 0.0165 | 1.6700 | -6.1407 | 0.9900 | 7.8106 | -75.4760 | -29.1391 | -1.3321 | -1.3146 | | 0.0005 | 10.3333 | 775 | 0.0164 | 1.6769 | -6.1401 | 0.9900 | 7.8170 | -75.4749 | -29.1251 | -1.3321 | -1.3146 | | 0.0185 | 10.6667 | 800 | 0.0164 | 1.6763 | -6.1561 | 0.9900 | 7.8324 | -75.5069 | -29.1265 | -1.3322 | -1.3146 | | 0.0212 | 11.0 | 825 | 0.0162 | 1.6734 | -6.1441 | 0.9900 | 7.8175 | -75.4828 | -29.1321 | -1.3322 | -1.3145 | | 0.0011 | 11.3333 | 850 | 0.0159 | 1.6707 | -6.1474 | 0.9900 | 7.8181 | -75.4894 | -29.1376 | -1.3321 | -1.3145 | | 0.0361 | 11.6667 | 875 | 0.0165 | 1.6746 | -6.1464 | 0.9900 | 7.8209 | -75.4874 | -29.1299 | -1.3322 | -1.3147 | | 0.0029 | 12.0 | 900 | 0.0161 | 1.6773 | -6.1406 | 0.9900 | 7.8179 | -75.4759 | -29.1244 | -1.3321 | -1.3146 | | 0.019 | 12.3333 | 925 | 0.0163 | 1.6716 | -6.1497 | 0.9900 | 7.8213 | -75.4941 | -29.1358 | -1.3321 | -1.3146 | | 0.0204 | 12.6667 | 950 | 0.0164 | 1.6699 | -6.1458 | 0.9900 | 7.8157 | -75.4864 | -29.1393 | -1.3321 | -1.3145 | | 0.0395 | 13.0 | 975 | 0.0164 | 1.6699 | -6.1458 | 0.9900 | 7.8157 | -75.4864 | -29.1393 | -1.3321 | -1.3145 | | 0.0048 | 13.3333 | 1000 | 0.0164 | 1.6699 | -6.1458 | 0.9900 | 7.8157 | -75.4864 | -29.1393 | -1.3321 | -1.3145 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1

ZON8955/uuu_fine_tune_taipower

ZON8955

2024-06-05T04:24:07Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:50:52Z

--- license: apache-2.0 ---

Ponrudee/Custom_tiger_google_vit-base-patch16-224

Ponrudee

2024-06-05T04:21:37Z

218

0

transformers

[ "transformers", "safetensors", "vit", "image-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

2024-06-05T04:20:59Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

Jongruk/custom-resnet18-model

Jongruk

2024-06-05T04:20:28Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:30:39Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

ChenWeiLi/Taiwan-inquiry_7B_v2.1

ChenWeiLi

2024-06-05T04:19:31Z

13

1

transformers

[ "transformers", "safetensors", "mistral", "text-generation", "Doctor_consultation", "Taiwan", "fine-tuning", "medicine", "conversational", "zh", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-04-17T06:02:25Z

--- license: apache-2.0 language: - zh library_name: transformers pipeline_tag: text-generation tags: - Doctor_consultation - Taiwan - fine-tuning - medicine --- # 🔎 Taiwan-inquiry_7B_v_2.1  "The model was fine-tuned based on the **Breeze-7B-Instruct-v1_0** model using a dataset that includes 614 authentic dialogues from the National Cheng Kung University Hospital. Additionally, 336 synthetic dialogues were included in the training set, carefully crafted to encompass themes drawn from sample questions of the OSCE (臨床技能測驗) sample questions in Taiwan. These synthetic dialogues were generated using GPT-3.5, Gemini-Pro and Breexe-8x7B-Instruct-v0_1. The training process was geared towards simulating verbal exchanges between doctors and patients within a hospital environment." <img src="https://cdn-uploads.huggingface.co/production/uploads/65c07d1b2357c1bded7a92fa/e7QbiYh07kcGwyKniAo0e.png" alt="image/png" style="width:80%; height:auto;"> **************************** **Updates** **************************** * 2024/04/25 🎉 Released [Taiwan-inquiry_7B_v2.1-awq](https://huggingface.co/ChenWeiLi/Taiwan-inquiry_7B_v2.1-awq) * 2024/04/29 🎉 Released [Taiwan-inquiry_7B_v2.1.gguf](https://huggingface.co/ChenWeiLi/Taiwan-inquiry_7B_v2.1.gguf) ### Model Description  - **Developed by:** [Joseph (Chen-Wei) Li](https://www.linkedin.com/in/joseph-li-3a453b231/), researcher assistant from National Taiwan University Hospital. - **Model type:** A 7B parameter GPT-like model fine-tuned on a combination of private and synthetic dialogue datasets. - **Language(s) (NLP):** Traditional Chinese (zh-tw) - **Finetuned from model :** [Breeze-7B-Instruct-v1_0 ](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v1_0) ### Usage of the model - The user can take on the role of a doctor, and the model can engage in conversation with you as if it were a patient. - You can provide the model with a brief patient background in the system prompt, and the model will respond based on that prompt. **(using my patient generator: [**colab**](https://colab.research.google.com/drive/17MSob_tQ2hPtMBL0xOF2zzV6WWe4dEG6?usp=sharing))** - Directly asking the certain disease about the symptoms and the possible therapies.**（Warning: It's not medical advice!)** ### Model evaluation The model got the **TMMLU+** (0 shot) performance using [EleutherAI/lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) with default settings. |Details on TMMLU+ (0 shot): Model | Base Model | STEM | Social Science | Humanities | Other | AVG | |-----------------------------------------------------|:---------------------:|:---------------:|:--------------:|:----------:|:----------:|:-------:| | Taiwan-inquiry_7B_v2.1 |Breeze-7B-Instruct-v1_0| 36.06 | 44.61 | 37.49 | 39.61 | 40.29 | | Taiwan-inquiry_7B_v2.0 |Breeze-7B-Instruct-v0_1| 36.17 | 43.59 | 35.45 | 37.63 | 38.95 | | Taiwan-inquiry_7B_v1.0 |Taiwan-LLM-7B-v2.1-chat| 26.74 | 29.47 | 26.83 | 29.61 | 28.83 | ### DEMO - **User: doctor** - **Chatbot: patient** ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65c07d1b2357c1bded7a92fa/Tp6ZKsGX1f2Qs5FLMFL51.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65c07d1b2357c1bded7a92fa/59A_3WFYl-h34g8XU1XGG.png)

tsavage68/UTI_L3_1000steps_1e8rate_05beta_CSFTDPO

tsavage68

2024-06-05T04:17:12Z

6

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T04:12:57Z

--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e8rate_05beta_CSFTDPO results: [] ---  # UTI_L3_1000steps_1e8rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6943 - Rewards/chosen: -0.0022 - Rewards/rejected: -0.0014 - Rewards/accuracies: 0.4700 - Rewards/margins: -0.0008 - Logps/rejected: -63.1976 - Logps/chosen: -32.4834 - Logits/rejected: -1.3229 - Logits/chosen: -1.3078 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-08 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6937 | 0.3333 | 25 | 0.6957 | -0.0013 | 0.0035 | 0.0500 | -0.0048 | -63.1876 | -32.4816 | -1.3228 | -1.3077 | | 0.6934 | 0.6667 | 50 | 0.6925 | -0.0026 | -0.0053 | 0.5100 | 0.0027 | -63.2053 | -32.4843 | -1.3228 | -1.3077 | | 0.6898 | 1.0 | 75 | 0.6961 | -0.0017 | 0.0030 | 0.4800 | -0.0047 | -63.1886 | -32.4823 | -1.3230 | -1.3078 | | 0.6855 | 1.3333 | 100 | 0.6937 | 0.0021 | 0.0020 | 0.5200 | 0.0001 | -63.1908 | -32.4748 | -1.3230 | -1.3079 | | 0.6852 | 1.6667 | 125 | 0.6971 | -0.0047 | 0.0016 | 0.4200 | -0.0062 | -63.1916 | -32.4884 | -1.3230 | -1.3078 | | 0.6879 | 2.0 | 150 | 0.6905 | 0.0038 | -0.0031 | 0.4500 | 0.0069 | -63.2009 | -32.4715 | -1.3231 | -1.3079 | | 0.6957 | 2.3333 | 175 | 0.6911 | -0.0001 | -0.0058 | 0.5200 | 0.0057 | -63.2062 | -32.4793 | -1.3230 | -1.3079 | | 0.6988 | 2.6667 | 200 | 0.6929 | -0.0035 | -0.0053 | 0.5300 | 0.0018 | -63.2052 | -32.4859 | -1.3229 | -1.3078 | | 0.6926 | 3.0 | 225 | 0.6903 | 0.0001 | -0.0071 | 0.5 | 0.0072 | -63.2088 | -32.4787 | -1.3230 | -1.3078 | | 0.6895 | 3.3333 | 250 | 0.6896 | -0.0014 | -0.0101 | 0.5 | 0.0087 | -63.2149 | -32.4818 | -1.3230 | -1.3079 | | 0.6988 | 3.6667 | 275 | 0.6932 | -0.0029 | -0.0044 | 0.5 | 0.0015 | -63.2034 | -32.4847 | -1.3231 | -1.3079 | | 0.6719 | 4.0 | 300 | 0.6895 | -0.0022 | -0.0107 | 0.4900 | 0.0085 | -63.2161 | -32.4833 | -1.3230 | -1.3079 | | 0.6988 | 4.3333 | 325 | 0.6886 | 0.0061 | -0.0045 | 0.5100 | 0.0106 | -63.2038 | -32.4668 | -1.3231 | -1.3080 | | 0.6859 | 4.6667 | 350 | 0.6869 | 0.0014 | -0.0126 | 0.5500 | 0.0139 | -63.2198 | -32.4762 | -1.3231 | -1.3080 | | 0.6922 | 5.0 | 375 | 0.6888 | -0.0004 | -0.0102 | 0.5 | 0.0097 | -63.2150 | -32.4799 | -1.3230 | -1.3079 | | 0.6937 | 5.3333 | 400 | 0.6875 | 0.0028 | -0.0102 | 0.5400 | 0.0130 | -63.2150 | -32.4734 | -1.3231 | -1.3080 | | 0.6773 | 5.6667 | 425 | 0.6857 | 0.0025 | -0.0143 | 0.5300 | 0.0168 | -63.2233 | -32.4741 | -1.3228 | -1.3078 | | 0.684 | 6.0 | 450 | 0.6900 | 0.0039 | -0.0036 | 0.5400 | 0.0075 | -63.2019 | -32.4713 | -1.3231 | -1.3079 | | 0.6914 | 6.3333 | 475 | 0.6902 | 0.0001 | -0.0078 | 0.5300 | 0.0079 | -63.2103 | -32.4789 | -1.3230 | -1.3079 | | 0.6879 | 6.6667 | 500 | 0.6871 | 0.0049 | -0.0084 | 0.5300 | 0.0133 | -63.2115 | -32.4691 | -1.3229 | -1.3078 | | 0.6934 | 7.0 | 525 | 0.6896 | 0.0039 | -0.0046 | 0.4900 | 0.0085 | -63.2039 | -32.4712 | -1.3230 | -1.3079 | | 0.6887 | 7.3333 | 550 | 0.6901 | 0.0037 | -0.0042 | 0.5200 | 0.0079 | -63.2031 | -32.4717 | -1.3230 | -1.3079 | | 0.6863 | 7.6667 | 575 | 0.6909 | -0.0015 | -0.0071 | 0.5800 | 0.0057 | -63.2090 | -32.4819 | -1.3230 | -1.3079 | | 0.6809 | 8.0 | 600 | 0.6895 | -0.0005 | -0.0093 | 0.5500 | 0.0088 | -63.2133 | -32.4801 | -1.3229 | -1.3077 | | 0.6879 | 8.3333 | 625 | 0.6906 | 0.0042 | -0.0019 | 0.5200 | 0.0061 | -63.1984 | -32.4706 | -1.3230 | -1.3079 | | 0.6844 | 8.6667 | 650 | 0.6865 | -0.0004 | -0.0156 | 0.5100 | 0.0152 | -63.2259 | -32.4798 | -1.3229 | -1.3079 | | 0.6945 | 9.0 | 675 | 0.6899 | -0.0047 | -0.0124 | 0.5500 | 0.0077 | -63.2195 | -32.4884 | -1.3230 | -1.3079 | | 0.6918 | 9.3333 | 700 | 0.6859 | 0.0034 | -0.0127 | 0.5400 | 0.0160 | -63.2200 | -32.4723 | -1.3230 | -1.3079 | | 0.6848 | 9.6667 | 725 | 0.6909 | -0.0053 | -0.0113 | 0.5200 | 0.0060 | -63.2172 | -32.4896 | -1.3229 | -1.3078 | | 0.6801 | 10.0 | 750 | 0.6915 | 0.0025 | -0.0025 | 0.5300 | 0.0049 | -63.1997 | -32.4741 | -1.3229 | -1.3078 | | 0.684 | 10.3333 | 775 | 0.6939 | -0.0003 | -0.0002 | 0.4900 | -0.0001 | -63.1951 | -32.4797 | -1.3229 | -1.3078 | | 0.6891 | 10.6667 | 800 | 0.6936 | -0.0012 | -0.0017 | 0.4900 | 0.0005 | -63.1981 | -32.4814 | -1.3229 | -1.3078 | | 0.6883 | 11.0 | 825 | 0.6943 | -0.0022 | -0.0014 | 0.4700 | -0.0008 | -63.1976 | -32.4834 | -1.3229 | -1.3078 | | 0.6969 | 11.3333 | 850 | 0.6943 | -0.0022 | -0.0014 | 0.4700 | -0.0008 | -63.1976 | -32.4834 | -1.3229 | -1.3078 | | 0.6984 | 11.6667 | 875 | 0.6943 | -0.0022 | -0.0014 | 0.4700 | -0.0008 | -63.1976 | -32.4834 | -1.3229 | -1.3078 | | 0.6937 | 12.0 | 900 | 0.6943 | -0.0022 | -0.0014 | 0.4700 | -0.0008 | -63.1976 | -32.4834 | -1.3229 | -1.3078 | | 0.684 | 12.3333 | 925 | 0.6943 | -0.0022 | -0.0014 | 0.4700 | -0.0008 | -63.1976 | -32.4834 | -1.3229 | -1.3078 | | 0.682 | 12.6667 | 950 | 0.6943 | -0.0022 | -0.0014 | 0.4700 | -0.0008 | -63.1976 | -32.4834 | -1.3229 | -1.3078 | | 0.6863 | 13.0 | 975 | 0.6943 | -0.0022 | -0.0014 | 0.4700 | -0.0008 | -63.1976 | -32.4834 | -1.3229 | -1.3078 | | 0.6836 | 13.3333 | 1000 | 0.6943 | -0.0022 | -0.0014 | 0.4700 | -0.0008 | -63.1976 | -32.4834 | -1.3229 | -1.3078 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1

PhillipGuo/hp-lat-llama-PCA-epsilon6.0-pgd_layer8_16-def_layer8-wikitext-28

PhillipGuo

2024-06-05T04:14:35Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T04:14:26Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

panit/custom-resnet18-model

panit

2024-06-05T04:12:32Z

81

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:59:11Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

rishisim/q-FrozenLake-v1-4x4-noSlippery

rishisim

2024-06-05T04:11:25Z

0

null

[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]

reinforcement-learning

2024-06-05T04:08:17Z

--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **FrozenLake-v1** This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** . ## Usage ```python model = load_from_hub(repo_id="rishisim/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```

kanitthong/custom-resnet18-model

kanitthong

2024-06-05T04:10:07Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T04:08:41Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

warwavn/custom-resnet18-model

warwavn

2024-06-05T04:08:07Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:59:35Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

kikikara/llama_with_eeve_the_third

kikikara

2024-06-05T04:05:00Z

142

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "trl", "sft", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T04:03:39Z

--- library_name: transformers tags: - trl - sft --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

WriLee/custom-resnet18-model

WriLee

2024-06-05T04:04:47Z

80

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:55:11Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

richardkelly/Qwen-Qwen1.5-1.8B-1717554065

richardkelly

2024-06-05T04:04:43Z

198

0

transformers

[ "transformers", "safetensors", "qwen2", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T02:21:05Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

Preeda/custom-resnet18-model-2

Preeda

2024-06-05T04:04:43Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T04:04:34Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

Tsover/custom-resnet18-model

Tsover

2024-06-05T04:03:13Z

81

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:51:30Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

PhillipGuo/hp-lat-llama-PCA-epsilon6.0-pgd_layer8_16-def_layer8-wikitext-27

PhillipGuo

2024-06-05T04:02:53Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T04:02:44Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-28

PhillipGuo

2024-06-05T04:02:40Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T04:02:30Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

superdavidyeh/uuu_fine_tune_gpt2

superdavidyeh

2024-06-05T04:01:34Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:02:18Z

--- license: apache-2.0 ---

thanaporn/kwang-resnet18-model

thanaporn

2024-06-05T04:01:32Z

81

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:58:11Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

cutedogspark/uuu_fine_tune_gpt2

cutedogspark

2024-06-05T04:00:19Z

145

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:02:14Z

--- license: apache-2.0 ---

temporary0-0name/pragna_with_adapt2

temporary0-0name

2024-06-05T04:00:11Z

128

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:46:59Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-27

PhillipGuo

2024-06-05T03:59:11Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:59:01Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

PhillipGuo/hp-lat-llama-PCA-epsilon0.5-pgd_layer8_16-def_layer8-wikitext-27

PhillipGuo

2024-06-05T03:59:10Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:59:01Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

tsavage68/UTI_M2_50steps_1e6rate_05beta_CSFTDPO

tsavage68

2024-06-05T03:58:05Z

6

0

transformers

[ "transformers", "safetensors", "mistral", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_M2_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_M2_1000steps_1e5rate_SFT", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:52:41Z

--- license: apache-2.0 base_model: tsavage68/UTI_M2_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_M2_50steps_1e6rate_05beta_CSFTDPO results: [] ---  # UTI_M2_50steps_1e6rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_M2_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_M2_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0694 - Rewards/chosen: 1.8275 - Rewards/rejected: -9.1239 - Rewards/accuracies: 0.9000 - Rewards/margins: 10.9514 - Logps/rejected: -62.4139 - Logps/chosen: -16.6395 - Logits/rejected: -3.8318 - Logits/chosen: -3.7514 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-06 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.314 | 0.3333 | 25 | 0.1006 | 1.1509 | -3.4985 | 0.9000 | 4.6494 | -51.1631 | -17.9927 | -3.8266 | -3.7515 | | 0.0175 | 0.6667 | 50 | 0.0694 | 1.8275 | -9.1239 | 0.9000 | 10.9514 | -62.4139 | -16.6395 | -3.8318 | -3.7514 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1

Manirathinam21/zephyr-7b-finetuned-support-chatbot

Manirathinam21

2024-06-05T03:57:45Z

1

0

peft

[ "peft", "tensorboard", "safetensors", "trl", "sft", "generated_from_trainer", "base_model:TheBloke/zephyr-7B-alpha-GPTQ", "base_model:adapter:TheBloke/zephyr-7B-alpha-GPTQ", "license:mit", "region:us" ]

null

2024-06-05T03:24:54Z

--- license: mit library_name: peft tags: - trl - sft - generated_from_trainer base_model: TheBloke/zephyr-7B-alpha-GPTQ model-index: - name: zephyr-7b-finetuned-support-chatbot results: [] ---  # zephyr-7b-finetuned-support-chatbot This model is a fine-tuned version of [TheBloke/zephyr-7B-alpha-GPTQ](https://huggingface.co/TheBloke/zephyr-7B-alpha-GPTQ) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 250 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.11.1 - Transformers 4.41.1 - Pytorch 2.3.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1

brax2005/Brax

brax2005

2024-06-05T03:55:24Z

0

fastai

[ "fastai", "climate", "text2text-generation", "ak", "dataset:H-D-T/Buzz", "arxiv:1910.09700", "license:bigscience-openrail-m", "region:us" ]

text2text-generation

2024-06-05T03:54:20Z

--- license: bigscience-openrail-m datasets: - H-D-T/Buzz language: - ak metrics: - cer library_name: fastai pipeline_tag: text2text-generation tags: - climate --- # Model Card for Model ID  This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). ## Model Details ### Model Description  - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

Allister7274/GIDEONunit

Allister7274

2024-06-05T03:48:18Z

0

null

[ "region:us" ]

null

2024-06-05T03:34:12Z

--- license: wtfpl datasets: - openbmb/RLAIF-V-Dataset language: - en metrics: - character tags: - documentation ---Adio-To-Text Text-To-Audio Voice-Analsis import speech_recognition as sr class GIDEONunit: def __init__(self): pass def transcribe_audio(self, audio_file): recognizer = sr.Recognizer() # Load audio file with sr.AudioFile(audio_file) as source: audio_data = recognizer.record(source) try: # Convert speech to text text = recognizer.recognize_google(audio_data) return text except sr.UnknownValueError: print("GIDEONunit could not understand the audio.") return "" except sr.RequestError as e: print(f"Could not request results from Google Speech Recognition service; {e}") return "" def create_documentation(self, audio_file, output_file): # Transcribe audio to text text = self.transcribe_audio(audio_file) # Write text to output file with open(output_file, "w") as f: f.write(text) # Example usage if __name__ == "__main__": gideon = GIDEONunit() audio_file = "input_audio.wav" output_file = "output_documentation.txt" gideon.create_documentation(audio_file, output_file)

RyanTsai0321/uuu_fine_tune_gpt2

RyanTsai0321

2024-06-05T03:45:50Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:01:04Z

--- license: apache-2.0 ---

siaowei-test/uuu_fine_tune_gpt2

siaowei-test

2024-06-05T03:45:28Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:17:53Z

--- license: apache-2.0 ---

ZaqAttack/bert-finetuned-ner

ZaqAttack

2024-06-05T03:45:10Z

62

0

transformers

[ "transformers", "tf", "bert", "token-classification", "generated_from_keras_callback", "base_model:google-bert/bert-base-cased", "base_model:finetune:google-bert/bert-base-cased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

token-classification

2024-06-04T22:24:15Z

--- license: apache-2.0 base_model: bert-base-cased tags: - generated_from_keras_callback model-index: - name: ZaqAttack/bert-finetuned-ner results: [] ---  # ZaqAttack/bert-finetuned-ner This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0477 - Validation Loss: 0.0576 - Epoch: 1 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2634, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: mixed_float16 ### Training results | Train Loss | Validation Loss | Epoch | |:----------:|:---------------:|:-----:| | 0.1778 | 0.0689 | 0 | | 0.0477 | 0.0576 | 1 | ### Framework versions - Transformers 4.41.1 - TensorFlow 2.15.0 - Datasets 2.19.2 - Tokenizers 0.19.1

Felix-Jas/uuu_fine_tune_gpt2

Felix-Jas

2024-06-05T03:44:55Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:18:18Z

--- license: apache-2.0 ---

PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-26

PhillipGuo

2024-06-05T03:44:45Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:44:35Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

PhillipGuo/hp-lat-llama-PCA-epsilon0.5-pgd_layer8_16-def_layer8-wikitext-26

PhillipGuo

2024-06-05T03:43:57Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:43:47Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

XBLUECATX/KeypointRCNN_Pretrained

XBLUECATX

2024-06-05T03:41:45Z

0

null

[ "license:llama3", "region:us" ]

null

2024-06-05T03:38:29Z

--- license: llama3 --- This weight is pre-trained for Keypoint Detection Tutorial usage. Incase the students cannot train due to hardware limitation or other issues. https://github.com/xxBLUECATxx/Simple_Keypoint_Detect

0xfaskety/Qwen-Qwen1.5-7B-1717558334

0xfaskety

2024-06-05T03:38:58Z

8

0

transformers

[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:32:17Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

PhillipGuo/hp-lat-llama-PCA-epsilon6.0-pgd_layer8_16-def_layer8-wikitext-25

PhillipGuo

2024-06-05T03:36:18Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:36:08Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

gaminwu/gpt2_finetuned_medical

gaminwu

2024-06-05T03:35:36Z

145

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:34:27Z

--- license: apache-2.0 ---

DuridMing/uuu_fine_tune_taipower

DuridMing

2024-06-05T03:35:25Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:01:53Z

--- license: apache-2.0 ---

JJ1970/uuu_fine_tune_taipower

JJ1970

2024-06-05T03:35:06Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:27:38Z

--- license: apache-2.0 ---

Chanchaiw/custom-resnet18-model

Chanchaiw

2024-06-05T03:32:52Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:58:51Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

Preeda/custom-resnet18-model-1

Preeda

2024-06-05T03:30:45Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:30:36Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-25

PhillipGuo

2024-06-05T03:28:54Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:28:44Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

Preeda/custom-resnet18-model

Preeda

2024-06-05T03:28:14Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:04:46Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

Airtan23/custom-resnet18-model-ex2

Airtan23

2024-06-05T03:27:18Z

80

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:27:11Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

siaowei-test/uuu_fine_tune_taipower

siaowei-test

2024-06-05T03:27:15Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:14:49Z

--- license: apache-2.0 ---

Felix-Jas/uuu_fine_tune_taipower

Felix-Jas

2024-06-05T03:25:49Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:18:06Z

--- license: apache-2.0 ---

PhillipGuo/hp-lat-llama-PCA-epsilon0.5-pgd_layer8_16-def_layer8-wikitext-25

PhillipGuo

2024-06-05T03:25:20Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:25:11Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

PhillipGuo/hp-lat-llama-PCA-epsilon3.0-pgd_layer8_16-def_layer8-wikitext-24

PhillipGuo

2024-06-05T03:22:42Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:22:33Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

Hannanana/uuu_fine_tune_taipower

Hannanana

2024-06-05T03:21:52Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:00:38Z

--- license: apache-2.0 ---

nuttcutee/nut-resnet18-model

nuttcutee

2024-06-05T03:21:48Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:59:33Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

tsavage68/UTI_L3_1000steps_1e8rate_03beta_CSFTDPO

tsavage68

2024-06-05T03:21:22Z

7

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:16:45Z

--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e8rate_03beta_CSFTDPO results: [] ---  # UTI_L3_1000steps_1e8rate_03beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6892 - Rewards/chosen: 0.0019 - Rewards/rejected: -0.0064 - Rewards/accuracies: 0.6200 - Rewards/margins: 0.0083 - Logps/rejected: -63.2161 - Logps/chosen: -32.4727 - Logits/rejected: -1.3229 - Logits/chosen: -1.3077 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-08 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6937 | 0.3333 | 25 | 0.6946 | -0.0008 | 0.0021 | 0.0600 | -0.0029 | -63.1876 | -32.4816 | -1.3229 | -1.3077 | | 0.6914 | 0.6667 | 50 | 0.6957 | -0.0038 | 0.0008 | 0.4400 | -0.0046 | -63.1920 | -32.4917 | -1.3228 | -1.3077 | | 0.691 | 1.0 | 75 | 0.6939 | -0.0059 | -0.0048 | 0.4400 | -0.0011 | -63.2107 | -32.4987 | -1.3231 | -1.3080 | | 0.6895 | 1.3333 | 100 | 0.6936 | -0.0030 | -0.0027 | 0.4600 | -0.0004 | -63.2035 | -32.4892 | -1.3230 | -1.3079 | | 0.6875 | 1.6667 | 125 | 0.6931 | 0.0025 | 0.0020 | 0.5100 | 0.0006 | -63.1881 | -32.4706 | -1.3230 | -1.3079 | | 0.6949 | 2.0 | 150 | 0.6956 | 0.0004 | 0.0046 | 0.4400 | -0.0042 | -63.1792 | -32.4777 | -1.3229 | -1.3078 | | 0.6996 | 2.3333 | 175 | 0.6922 | -0.0011 | -0.0034 | 0.5 | 0.0023 | -63.2060 | -32.4828 | -1.3229 | -1.3078 | | 0.691 | 2.6667 | 200 | 0.6933 | 0.0001 | 0.0001 | 0.5200 | -0.0000 | -63.1942 | -32.4786 | -1.3230 | -1.3079 | | 0.6879 | 3.0 | 225 | 0.6925 | -0.0011 | -0.0031 | 0.5400 | 0.0020 | -63.2049 | -32.4826 | -1.3230 | -1.3079 | | 0.691 | 3.3333 | 250 | 0.6907 | 0.0015 | -0.0040 | 0.4900 | 0.0055 | -63.2080 | -32.4741 | -1.3229 | -1.3079 | | 0.6953 | 3.6667 | 275 | 0.6924 | 0.0027 | 0.0008 | 0.4700 | 0.0019 | -63.1921 | -32.4699 | -1.3229 | -1.3078 | | 0.6906 | 4.0 | 300 | 0.6906 | -0.0010 | -0.0066 | 0.5200 | 0.0056 | -63.2167 | -32.4825 | -1.3230 | -1.3079 | | 0.6973 | 4.3333 | 325 | 0.6879 | 0.0027 | -0.0083 | 0.6100 | 0.0111 | -63.2224 | -32.4699 | -1.3229 | -1.3078 | | 0.6887 | 4.6667 | 350 | 0.6875 | 0.0051 | -0.0066 | 0.5900 | 0.0118 | -63.2168 | -32.4619 | -1.3230 | -1.3078 | | 0.6891 | 5.0 | 375 | 0.6887 | 0.0018 | -0.0076 | 0.5800 | 0.0093 | -63.2199 | -32.4732 | -1.3228 | -1.3077 | | 0.6961 | 5.3333 | 400 | 0.6906 | 0.0023 | -0.0033 | 0.5700 | 0.0055 | -63.2056 | -32.4714 | -1.3230 | -1.3079 | | 0.6848 | 5.6667 | 425 | 0.6902 | 0.0003 | -0.0061 | 0.5200 | 0.0064 | -63.2151 | -32.4779 | -1.3229 | -1.3078 | | 0.6855 | 6.0 | 450 | 0.6883 | 0.0021 | -0.0083 | 0.5600 | 0.0104 | -63.2224 | -32.4722 | -1.3230 | -1.3079 | | 0.6898 | 6.3333 | 475 | 0.6922 | -0.0013 | -0.0038 | 0.5300 | 0.0026 | -63.2075 | -32.4832 | -1.3229 | -1.3078 | | 0.6887 | 6.6667 | 500 | 0.6905 | 0.0023 | -0.0037 | 0.5400 | 0.0060 | -63.2071 | -32.4715 | -1.3229 | -1.3078 | | 0.6918 | 7.0 | 525 | 0.6862 | 0.0033 | -0.0110 | 0.5900 | 0.0144 | -63.2315 | -32.4679 | -1.3231 | -1.3080 | | 0.6871 | 7.3333 | 550 | 0.6902 | 0.0020 | -0.0043 | 0.5300 | 0.0063 | -63.2090 | -32.4723 | -1.3229 | -1.3078 | | 0.6879 | 7.6667 | 575 | 0.6927 | -0.0028 | -0.0041 | 0.4800 | 0.0013 | -63.2085 | -32.4885 | -1.3229 | -1.3078 | | 0.6793 | 8.0 | 600 | 0.6925 | -0.0004 | -0.0022 | 0.4600 | 0.0018 | -63.2021 | -32.4805 | -1.3230 | -1.3079 | | 0.6918 | 8.3333 | 625 | 0.6904 | 0.0009 | -0.0052 | 0.5200 | 0.0060 | -63.2119 | -32.4762 | -1.3230 | -1.3079 | | 0.6887 | 8.6667 | 650 | 0.6896 | 0.0015 | -0.0061 | 0.5500 | 0.0076 | -63.2150 | -32.4739 | -1.3229 | -1.3078 | | 0.6965 | 9.0 | 675 | 0.6905 | -0.0013 | -0.0072 | 0.5600 | 0.0060 | -63.2188 | -32.4833 | -1.3230 | -1.3078 | | 0.6895 | 9.3333 | 700 | 0.6877 | 0.0038 | -0.0076 | 0.6200 | 0.0114 | -63.2200 | -32.4662 | -1.3229 | -1.3078 | | 0.6855 | 9.6667 | 725 | 0.6891 | 0.0014 | -0.0074 | 0.5500 | 0.0087 | -63.2192 | -32.4744 | -1.3229 | -1.3078 | | 0.6871 | 10.0 | 750 | 0.6879 | 0.0033 | -0.0077 | 0.5900 | 0.0110 | -63.2204 | -32.4679 | -1.3230 | -1.3078 | | 0.6887 | 10.3333 | 775 | 0.6881 | 0.0034 | -0.0072 | 0.6200 | 0.0106 | -63.2186 | -32.4675 | -1.3229 | -1.3077 | | 0.693 | 10.6667 | 800 | 0.6890 | 0.0023 | -0.0065 | 0.6200 | 0.0088 | -63.2163 | -32.4715 | -1.3229 | -1.3078 | | 0.6875 | 11.0 | 825 | 0.6892 | 0.0019 | -0.0064 | 0.6200 | 0.0083 | -63.2161 | -32.4727 | -1.3229 | -1.3077 | | 0.6895 | 11.3333 | 850 | 0.6892 | 0.0019 | -0.0064 | 0.6200 | 0.0083 | -63.2161 | -32.4727 | -1.3229 | -1.3077 | | 0.6887 | 11.6667 | 875 | 0.6892 | 0.0019 | -0.0064 | 0.6200 | 0.0083 | -63.2161 | -32.4727 | -1.3229 | -1.3077 | | 0.6918 | 12.0 | 900 | 0.6892 | 0.0019 | -0.0064 | 0.6200 | 0.0083 | -63.2161 | -32.4727 | -1.3229 | -1.3077 | | 0.6918 | 12.3333 | 925 | 0.6892 | 0.0019 | -0.0064 | 0.6200 | 0.0083 | -63.2161 | -32.4727 | -1.3229 | -1.3077 | | 0.6816 | 12.6667 | 950 | 0.6892 | 0.0019 | -0.0064 | 0.6200 | 0.0083 | -63.2161 | -32.4727 | -1.3229 | -1.3077 | | 0.6883 | 13.0 | 975 | 0.6892 | 0.0019 | -0.0064 | 0.6200 | 0.0083 | -63.2161 | -32.4727 | -1.3229 | -1.3077 | | 0.6883 | 13.3333 | 1000 | 0.6892 | 0.0019 | -0.0064 | 0.6200 | 0.0083 | -63.2161 | -32.4727 | -1.3229 | -1.3077 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1

Ponrudee/custom-resnet18-model

Ponrudee

2024-06-05T03:20:24Z

80

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:59:57Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

PhillipGuo/hp-lat-llama-PCA-epsilon1.5-pgd_layer8_16-def_layer8-wikitext-24

PhillipGuo

2024-06-05T03:17:42Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:17:33Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

mradermacher/Shiki-m7-GGUF

mradermacher

2024-06-05T03:17:15Z

19

0

transformers

[ "transformers", "gguf", "en", "base_model:Sao10K/Shiki-m7", "base_model:quantized:Sao10K/Shiki-m7", "license:cc-by-nc-4.0", "endpoints_compatible", "region:us" ]

null

2024-06-04T16:35:42Z

--- base_model: Sao10K/Shiki-m7 language: - en library_name: transformers license: cc-by-nc-4.0 quantized_by: mradermacher --- ## About      static quants of https://huggingface.co/Sao10K/Shiki-m7  weighted/imatrix quants are available at https://huggingface.co/mradermacher/Shiki-m7-i1-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) | Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q2_K.gguf) | Q2_K | 2.8 | | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.IQ3_XS.gguf) | IQ3_XS | 3.1 | | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q3_K_S.gguf) | Q3_K_S | 3.3 | | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.IQ3_S.gguf) | IQ3_S | 3.3 | beats Q3_K* | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.IQ3_M.gguf) | IQ3_M | 3.4 | | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q3_K_M.gguf) | Q3_K_M | 3.6 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q3_K_L.gguf) | Q3_K_L | 3.9 | | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.IQ4_XS.gguf) | IQ4_XS | 4.0 | | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q4_K_M.gguf) | Q4_K_M | 4.5 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q5_K_S.gguf) | Q5_K_S | 5.1 | | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q5_K_M.gguf) | Q5_K_M | 5.2 | | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q6_K.gguf) | Q6_K | 6.0 | very good quality | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.Q8_0.gguf) | Q8_0 | 7.8 | fast, best quality | | [GGUF](https://huggingface.co/mradermacher/Shiki-m7-GGUF/resolve/main/Shiki-m7.f16.gguf) | f16 | 14.6 | 16 bpw, overkill | Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.

tsavage68/UTI_L3_1000steps_1e5rate_05beta_CSFTDPO

tsavage68

2024-06-05T03:14:51Z

6

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "trl", "dpo", "generated_from_trainer", "conversational", "base_model:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "base_model:finetune:tsavage68/UTI_L3_1000steps_1e5rate_SFT", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:10:24Z

--- license: llama3 base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT tags: - trl - dpo - generated_from_trainer model-index: - name: UTI_L3_1000steps_1e5rate_05beta_CSFTDPO results: [] ---  # UTI_L3_1000steps_1e5rate_05beta_CSFTDPO This model is a fine-tuned version of [tsavage68/UTI_L3_1000steps_1e5rate_SFT](https://huggingface.co/tsavage68/UTI_L3_1000steps_1e5rate_SFT) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0069 - Rewards/chosen: 2.5286 - Rewards/rejected: -48.6639 - Rewards/accuracies: 0.9900 - Rewards/margins: 51.1926 - Logps/rejected: -160.5225 - Logps/chosen: -27.4217 - Logits/rejected: -1.3535 - Logits/chosen: -1.3136 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.0 | 0.6667 | 50 | 0.0071 | 1.6538 | -15.9005 | 0.9900 | 17.5543 | -94.9957 | -29.1714 | -1.3772 | -1.3510 | | 0.0173 | 1.3333 | 100 | 0.1641 | 5.8391 | -14.1581 | 0.9100 | 19.9972 | -91.5108 | -20.8008 | -1.4149 | -1.3894 | | 0.0347 | 2.0 | 150 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 | | 0.0 | 2.6667 | 200 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 | | 0.0173 | 3.3333 | 250 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 | | 0.0347 | 4.0 | 300 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 | | 0.0173 | 4.6667 | 350 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 | | 0.0173 | 5.3333 | 400 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4148 | -1.3535 | -1.3136 | | 0.0173 | 6.0 | 450 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4148 | -1.3535 | -1.3136 | | 0.0347 | 6.6667 | 500 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4148 | -1.3535 | -1.3136 | | 0.0 | 7.3333 | 550 | 0.0069 | 2.5319 | -48.6721 | 0.9900 | 51.2040 | -160.5388 | -27.4152 | -1.3535 | -1.3136 | | 0.0347 | 8.0 | 600 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 | | 0.0 | 8.6667 | 650 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 | | 0.0173 | 9.3333 | 700 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 | | 0.0 | 10.0 | 750 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 | | 0.0173 | 10.6667 | 800 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 | | 0.0 | 11.3333 | 850 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 | | 0.0 | 12.0 | 900 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 | | 0.0173 | 12.6667 | 950 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 | | 0.0 | 13.3333 | 1000 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.0.0+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1

HenryLau1103/uuu_fine_tune_taipower

HenryLau1103

2024-06-05T03:14:46Z

144

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-05T03:00:35Z

--- license: apache-2.0 ---

gaminwu/uuu_fine_tune_gpt2

gaminwu

2024-06-05T03:12:14Z

0

null

[ "license:apache-2.0", "region:us" ]

null

2024-06-05T03:12:13Z

--- license: apache-2.0 ---

PhillipGuo/hp-lat-llama-PCA-epsilon0.5-pgd_layer8_16-def_layer8-wikitext-24

PhillipGuo

2024-06-05T03:12:00Z

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:11:47Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

NoteEB/custom-resnet18-model-EB

NoteEB

2024-06-05T03:03:12Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:59:12Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

leon625/TEST

leon625

2024-06-05T03:02:41Z

0

null

[ "license:apache-2.0", "region:us" ]

null

2024-06-05T03:02:41Z

--- license: apache-2.0 ---

yehii/uuu_fine_tune_gpt2

yehii

2024-06-05T03:01:54Z

0

null

[ "license:apache-2.0", "region:us" ]

null

2024-06-05T03:01:54Z

--- license: apache-2.0 ---

cutedogspark/tcp2023

cutedogspark

2024-06-05T03:01:48Z

0

null

[ "license:apache-2.0", "region:us" ]

null

2024-06-05T03:01:48Z

--- license: apache-2.0 ---

Orion-zhen/Llama3-Chinese-Chat-emoji

Orion-zhen

2024-06-05T03:01:45Z

7

1

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "en", "zh", "dataset:shareAI/DPO-zh-en-emoji", "license:llama3", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-06-03T08:34:35Z

--- license: llama3 datasets: - shareAI/DPO-zh-en-emoji language: - en - zh --- # Llama3-Chinese-Chat-emoji 在原模型shenzhi-wang/Llama3-70B-Chinese-Chat的基础上使用shareAI/DPO-zh-en-emoji进行QLoRA微调而来, 希望能重现原版llama3喜欢小表情的习惯失败惹, 原模型emoji能力已经被抑制惹, DPO也调不出来惹(悲) 新模型指路[Orion-zhen/Llama3-70B-Orion-Chinese](https://huggingface.co/Orion-zhen/Llama3-70B-Orion-Chinese)👈

DuridMing/tcp2024

DuridMing

2024-06-05T03:01:23Z

0

null

[ "license:apache-2.0", "region:us" ]

null

2024-06-05T03:01:23Z

--- license: apache-2.0 ---

superdavidyeh/tcp2023

superdavidyeh

2024-06-05T03:01:11Z

0

null

[ "license:apache-2.0", "region:us" ]

null

2024-06-05T03:01:11Z

--- license: apache-2.0 ---

Thanantikan/thannanthi-custom-resnet18-model

Thanantikan

2024-06-05T03:01:09Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T03:01:02Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

RyanTsai0321/tcp2024

RyanTsai0321

2024-06-05T03:00:33Z

0

null

[ "license:apache-2.0", "region:us" ]

null

2024-06-05T03:00:33Z

--- license: apache-2.0 ---

HenryLau1103/tcp2023

HenryLau1103

2024-06-05T03:00:24Z

0

null

[ "license:apache-2.0", "region:us" ]

null

2024-06-05T03:00:24Z

--- license: apache-2.0 ---

ManasaV22/fine_tuned_10012023

ManasaV22

2024-06-05T02:59:22Z

184

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-06-05T02:58:57Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

billkintao/billkintao-resnet18-model

billkintao

2024-06-05T02:59:12Z

79

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:59:05Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

rodrigoamf/ppo-LunarLander-v2

rodrigoamf

2024-06-05T02:58:07Z

0

stable-baselines3

[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]

reinforcement-learning

2024-06-05T01:05:01Z

--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 246.24 +/- 20.77 name: mean_reward verified: false --- # **PPO** Agent playing **LunarLander-v2** This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```

billkintao/custom-resnet18-model

billkintao

2024-06-05T02:58:04Z

80

0

transformers

[ "transformers", "safetensors", "pytorch_model_hub_mixin", "model_hub_mixin", "endpoints_compatible", "region:us" ]

null

2024-06-05T02:57:52Z

--- tags: - pytorch_model_hub_mixin - model_hub_mixin --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Library: [More Information Needed] - Docs: [More Information Needed]

LSHS/LSHS-Counselor-Bot

LSHS

2024-06-05T02:56:26Z

0

null

[ "document-question-answering", "arxiv:1910.09700", "license:afl-3.0", "region:us" ]

document-question-answering

2024-06-05T02:53:21Z

--- license: afl-3.0 pipeline_tag: document-question-answering --- # Model Card for Model ID  This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). ## Model Details ### Model Description  - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]