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train · 744k rows

modelId stringlengths 5 122	author stringlengths 2 42	last_modified timestamp[us, tz=UTC]	likes int64 0 11k	library_name stringclasses 245 values	tags sequencelengths 1 4.05k	pipeline_tag stringclasses 48 values	createdAt timestamp[us, tz=UTC]	card stringlengths 1 901k
aagarwalRT/llama-3-8B-q0f32	aagarwalRT	2024-07-02T11:29:19Z	0	null	[ "license:mit", "region:us" ]	null	2024-07-01T16:55:46Z	--- license: mit ---
kr-manish/distilgpt2-finetuned-rawHrPolicy1	kr-manish	2024-07-01T16:56:20Z	0	null	[ "region:us" ]	null	2024-07-01T16:56:20Z	Entry not found
Maulik1528/whisper-large-v2-ATCOSIM	Maulik1528	2024-07-01T16:57:52Z	0	null	[ "region:us" ]	null	2024-07-01T16:57:52Z	Entry not found
kr-manish/distilgpt2-finetuned-rawHrPolicyvf	kr-manish	2024-07-01T17:00:49Z	0	transformers	[ "transformers", "tf", "gpt2", "text-generation", "generated_from_keras_callback", "base_model:distilgpt2", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text-generation	2024-07-01T16:59:00Z	--- license: apache-2.0 base_model: distilgpt2 tags: - generated_from_keras_callback model-index: - name: kr-manish/distilgpt2-finetuned-rawHrPolicyvf 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. --> # kr-manish/distilgpt2-finetuned-rawHrPolicyvf This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 3.2382 - Epoch: 8 ## 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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Epoch \| \|:----------:\|:-----:\| \| 3.8398 \| 0 \| \| 3.6950 \| 1 \| \| 3.6270 \| 2 \| \| 3.5776 \| 3 \| \| 3.4771 \| 4 \| \| 3.4207 \| 5 \| \| 3.3600 \| 6 \| \| 3.2423 \| 7 \| \| 3.2382 \| 8 \| ### Framework versions - Transformers 4.41.2 - TensorFlow 2.15.0 - Datasets 2.20.0 - Tokenizers 0.19.1
Litzy619/MIS0630T5	Litzy619	2024-07-01T16:59:24Z	0	null	[ "region:us" ]	null	2024-07-01T16:59:24Z	Entry not found
mengshyu/Phi-3-vision-128k-instruct-q4f16_1-MLC	mengshyu	2024-07-01T17:02:02Z	0	null	[ "region:us" ]	null	2024-07-01T16:59:26Z	Entry not found
Litzy619/MIS0630T6	Litzy619	2024-07-01T21:12:57Z	0	null	[ "region:us" ]	null	2024-07-01T17:00:16Z	Entry not found
JoshKneale/q-FrozenLake-v1-4x4-noSlippery	JoshKneale	2024-07-01T17:01:53Z	0	null	[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2024-07-01T17:01:50Z	--- 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="JoshKneale/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"]) ```
necrobradley/my_awesome_face_model	necrobradley	2024-07-02T06:10:20Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "vit", "image-classification", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-07-01T17:02:00Z	Entry not found
BTX24/swin-tiny-patch4-window7-224-finetuned-birads-24	BTX24	2024-07-01T17:13:43Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "swin", "image-classification", "generated_from_trainer", "base_model:microsoft/swin-tiny-patch4-window7-224", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-07-01T17:02:46Z	--- license: apache-2.0 base_model: microsoft/swin-tiny-patch4-window7-224 tags: - generated_from_trainer metrics: - accuracy model-index: - name: swin-tiny-patch4-window7-224-finetuned-birads-24 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. --> # swin-tiny-patch4-window7-224-finetuned-birads-24 This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1073 - Accuracy: 0.4794 ## 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: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:------:\|:----:\|:---------------:\|:--------:\| \| 1.3421 \| 0.9756 \| 30 \| 1.3277 \| 0.3693 \| \| 1.2421 \| 1.9837 \| 61 \| 1.1846 \| 0.4587 \| \| 1.1991 \| 2.9919 \| 92 \| 1.1325 \| 0.4817 \| \| 1.1722 \| 4.0 \| 123 \| 1.1322 \| 0.4679 \| \| 1.1798 \| 4.9756 \| 153 \| 1.1013 \| 0.4954 \| \| 1.1525 \| 5.9837 \| 184 \| 1.1094 \| 0.4977 \| \| 1.1188 \| 6.9919 \| 215 \| 1.0942 \| 0.4931 \| \| 1.0973 \| 8.0 \| 246 \| 1.1091 \| 0.4748 \| \| 1.0742 \| 8.9756 \| 276 \| 1.1134 \| 0.4794 \| \| 1.0777 \| 9.7561 \| 300 \| 1.1073 \| 0.4794 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1
JoshKneale/q-Taxi-v3	JoshKneale	2024-07-01T17:04:14Z	0	null	[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2024-07-01T17:04:11Z	--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-Taxi-v3 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.50 +/- 2.65 name: mean_reward verified: false --- # Q-Learning Agent playing1 Taxi-v3 This is a trained model of a Q-Learning agent playing Taxi-v3 . ## Usage ```python model = load_from_hub(repo_id="JoshKneale/q-Taxi-v3", 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"]) ```
miservilla/esm2_t33_650M_UR50D-finetuned-localization-single-20240207	miservilla	2024-07-01T17:04:11Z	0	null	[ "region:us" ]	null	2024-07-01T17:04:11Z	Entry not found
nourheshamshaheen/llava_all_centralized_mistral_withouttags_1epoch	nourheshamshaheen	2024-07-02T22:00:37Z	0	transformers	[ "transformers", "safetensors", "llava_llama", "text-generation", "conversational", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-07-01T17:06:45Z	Entry not found
jiacheng8/client_1	jiacheng8	2024-07-01T18:20:22Z	0	null	[ "safetensors", "base_model:stabilityai/stable-diffusion-2-1-base", "license:creativeml-openrail-m", "region:us" ]	null	2024-07-01T17:07:53Z	--- license: creativeml-openrail-m base_model: stabilityai/stable-diffusion-2-1-base inference: true ---
fifala/20-fifa-07-01-02	fifala	2024-07-01T17:11:00Z	0	transformers	[ "transformers", "safetensors", "stablelm", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-07-01T17:08:22Z	Entry not found
PB7-DUT-2023/peft_Qwen2_7b_mt_v1_testt	PB7-DUT-2023	2024-07-01T17:09:56Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:09:40Z	--- 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]
manbeast3b/ZZZZZZZZdriver123	manbeast3b	2024-07-01T17:12:09Z	0	transformers	[ "transformers", "safetensors", "stablelm", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-07-01T17:09:49Z	Entry not found
JackBAI/general-off2on-filteredbc	JackBAI	2024-07-01T17:30:07Z	0	transformers	[ "transformers", "pytorch", "license:mit", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:09:53Z	--- license: mit ---
Maxivi/r	Maxivi	2024-07-01T19:11:32Z	0	null	[ "region:us" ]	null	2024-07-01T17:10:05Z	Entry not found
mjjj7/DANGEROUSERA	mjjj7	2024-07-01T17:11:05Z	0	null	[ "license:openrail", "region:us" ]	null	2024-07-01T17:10:30Z	--- license: openrail ---
davelotito/donut_experiment_bayesian_trial_20	davelotito	2024-07-01T17:56:42Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "vision-encoder-decoder", "generated_from_trainer", "base_model:naver-clova-ix/donut-base", "license:mit", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:11:14Z	--- license: mit base_model: naver-clova-ix/donut-base tags: - generated_from_trainer metrics: - bleu - wer model-index: - name: donut_experiment_bayesian_trial_20 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. --> # donut_experiment_bayesian_trial_20 This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6042 - Bleu: 0.0711 - Precisions: [0.8440748440748441, 0.7924528301886793, 0.7493188010899182, 0.7064516129032258] - Brevity Penalty: 0.0921 - Length Ratio: 0.2955 - Translation Length: 481 - Reference Length: 1628 - Cer: 0.7518 - Wer: 0.8208 ## 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: 1.4151037707088747e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 2 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Bleu \| Precisions \| Brevity Penalty \| Length Ratio \| Translation Length \| Reference Length \| Cer \| Wer \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\|:--------------------------------------------------------------------------------:\|:---------------:\|:------------:\|:------------------:\|:----------------:\|:------:\|:------:\| \| 0.0012 \| 1.0 \| 253 \| 0.6392 \| 0.0724 \| [0.8333333333333334, 0.7762237762237763, 0.7365591397849462, 0.6952380952380952] \| 0.0954 \| 0.2985 \| 486 \| 1628 \| 0.7482 \| 0.8193 \| \| 0.0068 \| 2.0 \| 506 \| 0.6212 \| 0.0697 \| [0.8413361169102297, 0.7867298578199052, 0.7452054794520548, 0.7012987012987013] \| 0.0908 \| 0.2942 \| 479 \| 1628 \| 0.7527 \| 0.8230 \| \| 0.0087 \| 3.0 \| 759 \| 0.6105 \| 0.0687 \| [0.83125, 0.7706855791962175, 0.726775956284153, 0.6828478964401294] \| 0.0915 \| 0.2948 \| 480 \| 1628 \| 0.7573 \| 0.8282 \| \| 0.0056 \| 4.0 \| 1012 \| 0.6042 \| 0.0711 \| [0.8440748440748441, 0.7924528301886793, 0.7493188010899182, 0.7064516129032258] \| 0.0921 \| 0.2955 \| 481 \| 1628 \| 0.7518 \| 0.8208 \| ### Framework versions - Transformers 4.40.0 - Pytorch 2.1.0 - Datasets 2.18.0 - Tokenizers 0.19.1
JackBAI/general-off2on-digirl	JackBAI	2024-07-01T17:47:54Z	0	transformers	[ "transformers", "pytorch", "license:mit", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:12:28Z	--- license: mit ---
healtori/19-heal-07-01-02	healtori	2024-07-01T17:16:38Z	0	transformers	[ "transformers", "safetensors", "stablelm", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-07-01T17:13:47Z	Entry not found
dhanishetty/before_test	dhanishetty	2024-07-01T17:34:31Z	0	transformers	[ "transformers", "safetensors", "phi3", "text-generation", "conversational", "custom_code", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]	text-generation	2024-07-01T17:14:47Z	--- 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]
dhanishetty/after_test	dhanishetty	2024-07-01T17:48:25Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:15:29Z	--- 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]
JackBAI/webshop-off2on-digirl	JackBAI	2024-07-01T17:47:12Z	0	transformers	[ "transformers", "pytorch", "license:mit", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:15:54Z	--- license: mit ---
Markell123/llama2-finetuning-conversational	Markell123	2024-07-02T17:02:29Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:16:01Z	--- 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]
JackBAI/webshop-off2on-filteredbc	JackBAI	2024-07-01T17:46:27Z	0	transformers	[ "transformers", "pytorch", "license:mit", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:18:03Z	--- license: mit ---
clinton07021996/naschainv141	clinton07021996	2024-07-01T17:18:34Z	0	null	[ "region:us" ]	null	2024-07-01T17:18:32Z	Entry not found
dmartincc/vet-sm	dmartincc	2024-07-02T12:50:53Z	0	transformers	[ "transformers", "safetensors", "vit", "image-classification", "generated_from_trainer", "dataset:imagefolder", "base_model:google/vit-base-patch16-224-in21k", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-07-01T17:20:33Z	--- license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: vet-sm results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.6771653543307087 --- <!-- 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. --> # vet-sm This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 1.0058 - Accuracy: 0.6772 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| 1.7243 \| 0.99 \| 67 \| 1.6282 \| 0.4829 \| \| 1.283 \| 2.0 \| 135 \| 1.3131 \| 0.5722 \| \| 0.9453 \| 2.99 \| 202 \| 1.1048 \| 0.6430 \| \| 0.7164 \| 4.0 \| 270 \| 1.0157 \| 0.6719 \| \| 0.5591 \| 4.96 \| 335 \| 1.0058 \| 0.6772 \| ### Framework versions - Transformers 4.38.2 - Pytorch 2.2.0 - Datasets 2.16.1 - Tokenizers 0.15.1
TomEijkelenkamp/renaissance-llava-contrast	TomEijkelenkamp	2024-07-01T17:20:40Z	0	null	[ "region:us" ]	null	2024-07-01T17:20:40Z	Entry not found
bartowski/Hathor_Aleph-L3-8B-v0.72-exl2	bartowski	2024-07-01T17:24:20Z	1	null	[ "text-generation", "en", "license:other", "region:us" ]	text-generation	2024-07-01T17:24:18Z	--- license: other language: - en quantized_by: bartowski pipeline_tag: text-generation --- ## Exllama v2 Quantizations of Hathor_Aleph-L3-8B-v0.72 Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.1.6">turboderp's ExLlamaV2 v0.1.6</a> for quantization. <b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b> Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions. Original model: https://huggingface.co/Nitral-AI/Hathor_Aleph-L3-8B-v0.72 ## Prompt format ``` <\|begin_of_text\|><\|start_header_id\|>system<\|end_header_id\|> {system_prompt}<\|eot_id\|><\|start_header_id\|>user<\|end_header_id\|> {prompt}<\|eot_id\|><\|start_header_id\|>assistant<\|end_header_id\|> ``` ## Available sizes \| Branch \| Bits \| lm_head bits \| VRAM (4k) \| VRAM (8K) \| VRAM (16k) \| VRAM (32k) \| Description \| \| ----- \| ---- \| ------- \| ------ \| ------ \| ------ \| ------ \| ------------ \| \| [8_0](https://huggingface.co/bartowski/Hathor_Aleph-L3-8B-v0.72-exl2/tree/8_0) \| 8.0 \| 8.0 \| 10.1 GB \| 10.5 GB \| 11.5 GB \| 13.6 GB \| Maximum quality that ExLlamaV2 can produce, near unquantized performance. \| \| [6_5](https://huggingface.co/bartowski/Hathor_Aleph-L3-8B-v0.72-exl2/tree/6_5) \| 6.5 \| 8.0 \| 8.9 GB \| 9.3 GB \| 10.3 GB \| 12.4 GB \| Very similar to 8.0, good tradeoff of size vs performance, recommended. \| \| [5_0](https://huggingface.co/bartowski/Hathor_Aleph-L3-8B-v0.72-exl2/tree/5_0) \| 5.0 \| 6.0 \| 7.7 GB \| 8.1 GB \| 9.1 GB \| 11.2 GB \| Slightly lower quality vs 6.5, but usable on 8GB cards. \| \| [4_25](https://huggingface.co/bartowski/Hathor_Aleph-L3-8B-v0.72-exl2/tree/4_25) \| 4.25 \| 6.0 \| 7.0 GB \| 7.4 GB \| 8.4 GB \| 10.5 GB \| GPTQ equivalent bits per weight, slightly higher quality. \| \| [3_5](https://huggingface.co/bartowski/Hathor_Aleph-L3-8B-v0.72-exl2/tree/3_5) \| 3.5 \| 6.0 \| 6.4 GB \| 6.8 GB \| 7.8 GB \| 9.9 GB \| Lower quality, only use if you have to. \| ## Download instructions With git: ```shell git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Hathor_Aleph-L3-8B-v0.72-exl2 Hathor_Aleph-L3-8B-v0.72-exl2-6_5 ``` With huggingface hub (credit to TheBloke for instructions): ```shell pip3 install huggingface-hub ``` To download a specific branch, use the `--revision` parameter. For example, to download the 6.5 bpw branch: Linux: ```shell huggingface-cli download bartowski/Hathor_Aleph-L3-8B-v0.72-exl2 --revision 6_5 --local-dir Hathor_Aleph-L3-8B-v0.72-exl2-6_5 ``` Windows (which apparently doesn't like _ in folders sometimes?): ```shell huggingface-cli download bartowski/Hathor_Aleph-L3-8B-v0.72-exl2 --revision 6_5 --local-dir Hathor_Aleph-L3-8B-v0.72-exl2-6.5 ``` Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski
Vyshnav-Unnikrishnan/SeminarTest	Vyshnav-Unnikrishnan	2024-07-01T17:25:46Z	0	null	[ "license:cc", "region:us" ]	null	2024-07-01T17:25:46Z	--- license: cc ---
mervinpraison/Florence-2-FT-DocVQA	mervinpraison	2024-07-01T19:11:27Z	0	transformers	[ "transformers", "safetensors", "florence2", "text-generation", "custom_code", "arxiv:1910.09700", "autotrain_compatible", "region:us" ]	text-generation	2024-07-01T17:26:17Z	--- 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]
jiacheng8/sd3-lora	jiacheng8	2024-07-01T17:57:43Z	0	null	[ "base_model:stabilityai/stable-diffusion-3-medium-diffusers", "license:creativeml-openrail-m", "region:us" ]	null	2024-07-01T17:26:22Z	--- license: creativeml-openrail-m base_model: stabilityai/stable-diffusion-3-medium-diffusers ---
clinton07021996/naschainv38	clinton07021996	2024-07-01T17:26:28Z	0	null	[ "region:us" ]	null	2024-07-01T17:26:26Z	Entry not found
naimul011/Imdb-Senti-llama3	naimul011	2024-07-01T17:27:46Z	0	null	[ "region:us" ]	null	2024-07-01T17:27:46Z	Entry not found
Alwahsh/llama-3-8b-70-base-quantized	Alwahsh	2024-07-01T17:48:53Z	0	transformers	[ "transformers", "openvino", "llama", "text-generation", "license:llama3", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text-generation	2024-07-01T17:29:11Z	--- license: llama3 --- llama-3-8b model with 70% sparsity based on wanda.
habulaj/498724470477	habulaj	2024-07-01T17:29:58Z	0	null	[ "region:us" ]	null	2024-07-01T17:29:40Z	Entry not found
mgh6/TCS_Pairing_SaProt	mgh6	2024-07-03T01:25:15Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "esm", "text-classification", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-07-01T17:29:53Z	Entry not found
TwentyNine/nllb-jpn-ain	TwentyNine	2024-07-03T00:47:10Z	0	transformers	[ "transformers", "pytorch", "m2m_100", "text2text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2024-07-01T17:30:54Z	Entry not found
zhhan/adapter-Phi-3-mini-4k-instruct_summarization	zhhan	2024-07-02T16:55:49Z	0	peft	[ "peft", "safetensors", "phi3", "summarization", "en", "dataset:zhhan/slimpajama_850m", "arxiv:1910.09700", "base_model:microsoft/Phi-3-mini-4k-instruct", "license:apache-2.0", "region:us" ]	summarization	2024-07-01T17:32:22Z	--- base_model: microsoft/Phi-3-mini-4k-instruct library_name: peft license: apache-2.0 datasets: - zhhan/slimpajama_850m language: - en pipeline_tag: summarization tags: - phi3 --- # 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. --> - Developed by: Zhipeng Han - Funded by: Microsoft - Model type: Adaptor of generation model - Language(s) (NLP): English - License: Apache license 2.0 - Finetuned from model: microsoft/Phi-3-mini-4k-instruct ## 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. --> This is fine-tuned adaptor based on the Phi-3-mini-4k-instruct. NOTICE This adaptor is fine tuned with the mini dataset of slimpajama and user should know that it is not ready for real product scenario. This adaptor is used for developing/testing llama.cpp features. ### 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] #### 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] ### Framework versions - PEFT 0.11.1
Makkoen/whisper-large-cit-synth-do015-wd0-lr5e-06-400	Makkoen	2024-07-01T18:32:09Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2024-07-01T17:32:55Z	Entry not found
habulaj/324722290941	habulaj	2024-07-01T17:33:15Z	0	null	[ "region:us" ]	null	2024-07-01T17:33:12Z	Entry not found
clinton07021996/naschainv40	clinton07021996	2024-07-01T17:33:42Z	0	null	[ "region:us" ]	null	2024-07-01T17:33:41Z	Entry not found
wiweka24/gemma-psychiatrist-v0-lora	wiweka24	2024-07-01T17:36:07Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "gemma", "trl", "en", "base_model:unsloth/gemma-7b-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:35:38Z	--- base_model: unsloth/gemma-7b-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - gemma - trl --- # Uploaded model - Developed by: wiweka24 - License: apache-2.0 - Finetuned from model : unsloth/gemma-7b-bnb-4bit This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
wiweka24/gemma-psychiatrist-v0-fp16	wiweka24	2024-07-01T17:45:46Z	0	transformers	[ "transformers", "pytorch", "gemma", "text-generation", "text-generation-inference", "unsloth", "trl", "sft", "en", "base_model:unsloth/gemma-7b-bnb-4bit", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-07-01T17:37:05Z	--- base_model: unsloth/gemma-7b-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - gemma - trl - sft --- # Uploaded model - Developed by: wiweka24 - License: apache-2.0 - Finetuned from model : unsloth/gemma-7b-bnb-4bit This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
ProElectro07/MeddBbott	ProElectro07	2024-07-01T17:37:43Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:37:25Z	--- 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. 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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]
clinton07021996/naschainv80	clinton07021996	2024-07-01T17:41:25Z	0	null	[ "region:us" ]	null	2024-07-01T17:41:23Z	Entry not found
VamshiVasam2806/batch-5-4001-5000	VamshiVasam2806	2024-07-01T17:42:38Z	0	peft	[ "peft", "safetensors", "trl", "sft", "generated_from_trainer", "base_model:microsoft/phi-2", "license:mit", "region:us" ]	null	2024-07-01T17:42:32Z	--- base_model: microsoft/phi-2 library_name: peft license: mit tags: - trl - sft - generated_from_trainer model-index: - name: batch-5-4001-5000 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. --> # batch-5-4001-5000 This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown 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: 2 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results ### Framework versions - PEFT 0.11.1 - Transformers 4.42.3 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1
streamtune/users-user123-2024-07-01-17-43-27	streamtune	2024-07-01T17:45:47Z	0	transformers	[ "transformers", "safetensors", "unsloth", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:43:27Z	--- library_name: transformers tags: - unsloth --- # 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. 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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]
AndreasThinks/Mistral-7B-v0.3-nopcsa-finetune	AndreasThinks	2024-07-01T17:44:09Z	0	null	[ "region:us" ]	null	2024-07-01T17:44:09Z	Entry not found
habulaj/1220612491	habulaj	2024-07-01T17:44:40Z	0	null	[ "region:us" ]	null	2024-07-01T17:44:34Z	Entry not found
KasuleTrevor/wav2vec2-large-xls-r-300m-lg-1hr-v6	KasuleTrevor	2024-07-01T18:35:43Z	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:45:37Z	--- 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]
noahtye/testcreatemodel-2024-07-01	noahtye	2024-07-01T17:46:17Z	0	null	[ "region:us" ]	null	2024-07-01T17:46:17Z	Entry not found
wiweka24/gemma-psychiatrist-v0-4bit	wiweka24	2024-07-01T17:55:51Z	0	transformers	[ "transformers", "safetensors", "gemma", "text-generation", "text-generation-inference", "unsloth", "trl", "sft", "en", "base_model:unsloth/gemma-7b-bnb-4bit", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]	text-generation	2024-07-01T17:46:32Z	--- base_model: unsloth/gemma-7b-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - gemma - trl - sft --- # Uploaded model - Developed by: wiweka24 - License: apache-2.0 - Finetuned from model : unsloth/gemma-7b-bnb-4bit This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
Makkoen/whisper-large-cit-synth-do015-wd0-lr3e-06-800	Makkoen	2024-07-01T18:47:41Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2024-07-01T17:46:51Z	Entry not found
zekriwap/zekrigpt	zekriwap	2024-07-01T17:49:57Z	0	null	[ "license:unknown", "region:us" ]	null	2024-07-01T17:49:57Z	--- license: unknown ---
Alwahsh/llama-3-8b-0-base-quantized	Alwahsh	2024-07-01T18:01:45Z	0	transformers	[ "transformers", "openvino", "llama", "text-generation", "license:llama3", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text-generation	2024-07-01T17:50:12Z	--- license: llama3 --- Base Llama3 model after quantization into Int8 in weights and activations.
dhanishetty/after_test_Just-model	dhanishetty	2024-07-01T17:52:38Z	0	transformers	[ "transformers", "safetensors", "phi3", "text-generation", "trl", "sft", "conversational", "custom_code", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]	text-generation	2024-07-01T17:50:42Z	--- 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]
mradermacher/Nimbus-Miqu-v0.1-70B-GGUF	mradermacher	2024-07-01T17:51:36Z	0	null	[ "region:us" ]	null	2024-07-01T17:51:33Z	<!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> static quants of https://huggingface.co/invisietch/Nimbus-Miqu-v0.1-70B
habulaj/199993210848	habulaj	2024-07-01T17:52:19Z	0	null	[ "region:us" ]	null	2024-07-01T17:52:11Z	Entry not found
YuvrajSingh9886/phi3-mini-instruct-alpaca-model	YuvrajSingh9886	2024-07-01T17:54:35Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:unsloth/phi-3-mini-4k-instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-07-01T17:52:58Z	--- base_model: unsloth/phi-3-mini-4k-instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - Developed by: YuvrajSingh9886 - License: apache-2.0 - Finetuned from model : unsloth/phi-3-mini-4k-instruct-bnb-4bit This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
lunarlist/summarize_02	lunarlist	2024-07-01T17:53:18Z	0	null	[ "region:us" ]	null	2024-07-01T17:53:18Z	Entry not found
habulaj/8152659135	habulaj	2024-07-01T17:54:17Z	0	null	[ "region:us" ]	null	2024-07-01T17:54:14Z	Entry not found
zhangduo4610/opt350mtst	zhangduo4610	2024-07-01T17:54:23Z	0	null	[ "region:us" ]	null	2024-07-01T17:54:23Z	Entry not found
habulaj/8677763650	habulaj	2024-07-01T17:55:17Z	0	null	[ "region:us" ]	null	2024-07-01T17:55:08Z	Entry not found
habulaj/129999104925	habulaj	2024-07-01T17:55:17Z	0	null	[ "region:us" ]	null	2024-07-01T17:55:15Z	Entry not found
sharmadhruv/qa_by_ernie_lora_weights	sharmadhruv	2024-07-01T17:58:59Z	0	null	[ "region:us" ]	null	2024-07-01T17:58:58Z	Entry not found
leeloli/sakura-hkt48-updated	leeloli	2024-07-01T17:59:44Z	0	null	[ "license:openrail", "region:us" ]	null	2024-07-01T17:59:06Z	--- license: openrail ---
robinhub/robin_model_beta	robinhub	2024-07-01T18:45:19Z	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "text-generation-inference", "unsloth", "trl", "conversational", "en", "base_model:taide/TAIDE-LX-7B-Chat", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-07-01T17:59:49Z	--- base_model: taide/TAIDE-LX-7B-Chat language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: robinhub - License: apache-2.0 - Finetuned from model : taide/TAIDE-LX-7B-Chat This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
maxseats/SungBeom-whisper-small-ko-set10-discard	maxseats	2024-07-01T18:09:15Z	0	transformers	[ "transformers", "safetensors", "whisper", "automatic-speech-recognition", "speech-recognition", "ko", "dataset:maxseats/aihub-464-preprocessed-680GB-set-10", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2024-07-01T18:01:05Z	--- language: ko tags: - whisper - speech-recognition datasets: - maxseats/aihub-464-preprocessed-680GB-set-10 metrics: - cer --- # Model Name : maxseats/SungBeom-whisper-small-ko-set9 # Description - 파인튜닝 데이터셋 : maxseats/aihub-464-preprocessed-680GB-set-10 # 설명 - AI hub의 주요 영역별 회의 음성 데이터셋을 학습 중이에요. - 680GB 중 set_0~9 데이터(100GB)까지 파인튜닝한 모델을 불러와서, set_10 데이터(10GB)를 학습한 모델입니다. - 링크 : https://huggingface.co/datasets/maxseats/aihub-464-preprocessed-680GB-set-10
ClaudiaRichard/CodeLlamaFinetuned_HumanEvalV1	ClaudiaRichard	2024-07-01T18:02:05Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T18:02:01Z	--- 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. 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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]
beckham20031992/naschainv160	beckham20031992	2024-07-02T17:17:35Z	0	null	[ "region:us" ]	null	2024-07-01T18:02:39Z	Entry not found
streamtune/4	streamtune	2024-07-01T18:08:44Z	0	transformers	[ "transformers", "safetensors", "unsloth", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T18:06:32Z	--- library_name: transformers tags: - unsloth --- # 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. 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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]
Samraat/paligemma_vqav2	Samraat	2024-07-01T18:06:33Z	0	null	[ "region:us" ]	null	2024-07-01T18:06:33Z	Entry not found
Samraat/pavqasam	Samraat	2024-07-01T18:08:43Z	0	null	[ "region:us" ]	null	2024-07-01T18:08:43Z	Entry not found
beckham20031992/naschainv102	beckham20031992	2024-07-01T18:12:57Z	0	null	[ "region:us" ]	null	2024-07-01T18:12:56Z	Entry not found
jssaluja/gly_ivw	jssaluja	2024-07-01T18:40:56Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-07-01T18:13:02Z	Entry not found
beckham20031992/naschainv125	beckham20031992	2024-07-01T18:13:16Z	0	null	[ "region:us" ]	null	2024-07-01T18:13:15Z	Entry not found
beckham20031992/naschainv69	beckham20031992	2024-07-01T18:13:37Z	0	null	[ "region:us" ]	null	2024-07-01T18:13:34Z	Entry not found
vgangal101/bert-finetuned-ner	vgangal101	2024-07-01T19:00:47Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "bert", "token-classification", "generated_from_trainer", "dataset:conll2003", "base_model:bert-base-cased", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]	token-classification	2024-07-01T18:17:31Z	--- license: apache-2.0 base_model: bert-base-cased tags: - generated_from_trainer datasets: - conll2003 metrics: - precision - recall - f1 - accuracy model-index: - name: bert-finetuned-ner results: - task: name: Token Classification type: token-classification dataset: name: conll2003 type: conll2003 config: conll2003 split: validation args: conll2003 metrics: - name: Precision type: precision value: 0.9376864434869076 - name: Recall type: recall value: 0.9522046449007069 - name: F1 type: f1 value: 0.9448897795591182 - name: Accuracy type: accuracy value: 0.9866368399364219 --- <!-- 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. --> # bert-finetuned-ner This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset. It achieves the following results on the evaluation set: - Loss: 0.0597 - Precision: 0.9377 - Recall: 0.9522 - F1: 0.9449 - Accuracy: 0.9866 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Precision \| Recall \| F1 \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:---------:\|:------:\|:------:\|:--------:\| \| 0.0758 \| 1.0 \| 1756 \| 0.0649 \| 0.9071 \| 0.9354 \| 0.9210 \| 0.9823 \| \| 0.0362 \| 2.0 \| 3512 \| 0.0635 \| 0.9368 \| 0.9478 \| 0.9423 \| 0.9857 \| \| 0.0217 \| 3.0 \| 5268 \| 0.0597 \| 0.9377 \| 0.9522 \| 0.9449 \| 0.9866 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1
AdamKasumovic/llama3-70b-instruct-ids-winogrande-train-s-zu-winogrande-high	AdamKasumovic	2024-07-01T18:35:42Z	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "text-generation-inference", "unsloth", "trl", "conversational", "en", "base_model:unsloth/llama-3-70b-Instruct-bnb-4bit", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-07-01T18:18:34Z	--- base_model: unsloth/llama-3-70b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: AdamKasumovic - License: apache-2.0 - Finetuned from model : unsloth/llama-3-70b-Instruct-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
beckham20031992/naschainv147	beckham20031992	2024-07-01T18:19:07Z	0	null	[ "region:us" ]	null	2024-07-01T18:19:06Z	Entry not found
streamtune/39814824-3752-46df-bd41-58db99c5706c	streamtune	2024-07-01T18:21:31Z	0	transformers	[ "transformers", "safetensors", "unsloth", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T18:19:15Z	--- library_name: transformers tags: - unsloth --- # 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]
K-Monitor/kmdb_classification_hubert	K-Monitor	2024-07-01T18:21:33Z	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-07-01T18:20:16Z	--- 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]
TeamLevel274/GPT2Model	TeamLevel274	2024-07-01T18:21:47Z	0	null	[ "license:gpl-2.0", "region:us" ]	null	2024-07-01T18:21:47Z	--- license: gpl-2.0 ---
Sridhar100/vit-base-patch16-224-finetuned-flower	Sridhar100	2024-07-01T18:35:20Z	0	transformers	[ "transformers", "pytorch", "vit", "image-classification", "generated_from_trainer", "dataset:imagefolder", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2024-07-01T18:24:11Z	--- license: apache-2.0 tags: - generated_from_trainer datasets: - imagefolder model-index: - name: vit-base-patch16-224-finetuned-flower 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. --> # vit-base-patch16-224-finetuned-flower This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder 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: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results ### Framework versions - Transformers 4.24.0 - Pytorch 2.3.0+cu121 - Datasets 2.7.1 - Tokenizers 0.13.3
Clebersla/Dave_Grohl_Drums_1994	Clebersla	2024-07-01T18:28:15Z	0	null	[ "region:us" ]	null	2024-07-01T18:26:57Z	Entry not found
abhayesian/LLama3_HarmBench_NoAttack	abhayesian	2024-07-01T18:28:20Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T18:27:58Z	--- 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]
CennetOguz/cooking_blip2_3	CennetOguz	2024-07-01T18:28:56Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T18:28:51Z	--- 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]
mdeputy/output	mdeputy	2024-07-02T22:43:23Z	0	transformers	[ "transformers", "safetensors", "Unet", "generated_from_trainer", "endpoints_compatible", "region:us" ]	null	2024-07-01T18:29:01Z	--- tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: output 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. --> # output This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5042 - Accuracy: 0.9932 - F1: 0.9911 - Iou: 0.9878 - Visualizations: ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] ## 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: 5e-05 - 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 - lr_scheduler_warmup_steps: 100 - num_epochs: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| F1 \| Iou \| Visualizations \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:------:\|:------:\|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:\| \| No log \| 1.0 \| 1 \| 0.6395 \| 0.9924 \| 0.9907 \| 0.9869 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| \| No log \| 2.0 \| 2 \| 0.6224 \| 0.9929 \| 0.9909 \| 0.9874 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| \| No log \| 3.0 \| 3 \| 0.6060 \| 0.9932 \| 0.9910 \| 0.9877 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| \| No log \| 4.0 \| 4 \| 0.5884 \| 0.9933 \| 0.9911 \| 0.9878 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| \| No log \| 5.0 \| 5 \| 0.5659 \| 0.9934 \| 0.9912 \| 0.9879 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| \| No log \| 6.0 \| 6 \| 0.5472 \| 0.9934 \| 0.9912 \| 0.9879 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| \| No log \| 7.0 \| 7 \| 0.5339 \| 0.9934 \| 0.9912 \| 0.9879 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| \| No log \| 8.0 \| 8 \| 0.5232 \| 0.9934 \| 0.9912 \| 0.9879 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| \| No log \| 9.0 \| 9 \| 0.5134 \| 0.9933 \| 0.9911 \| 0.9878 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| \| No log \| 10.0 \| 10 \| 0.5042 \| 0.9932 \| 0.9911 \| 0.9878 \| ['c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_0.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_1.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_2.png', 'c:/Users/Gleghorn/Documents/ComputerVision/visualizations\\visualization_sample_3.png'] \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1
habulaj/6864150818	habulaj	2024-07-01T18:31:13Z	0	null	[ "region:us" ]	null	2024-07-01T18:31:06Z	Entry not found
Random-cow-on-the-grass/RVCmodelsTITANretrains	Random-cow-on-the-grass	2024-07-01T20:09:36Z	0	null	[ "audio-to-audio", "en", "license:openrail", "region:us" ]	audio-to-audio	2024-07-01T18:32:25Z	--- license: openrail language: - en pipeline_tag: audio-to-audio --- This model page will have TITAN retrains of ALL my models that I have made. When RVC V3 comes out, this model page will become obsolete.
valerielucro/mistral_gsm8k_sft_v1_epoch1	valerielucro	2024-07-01T18:34:15Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-07-01T18:33:24Z	--- 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]
aishwarya1/to-pokemon	aishwarya1	2024-07-02T11:07:46Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "git", "text-generation", "generated_from_trainer", "base_model:microsoft/git-base", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-07-01T18:33:44Z	--- license: mit base_model: microsoft/git-base tags: - generated_from_trainer model-index: - name: to-pokemon 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. --> # to-pokemon This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 5.9259 - Wer Score: 16.3460 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer Score \| \|:-------------:\|:------:\|:----:\|:---------------:\|:---------:\| \| 7.5989 \| 3.5088 \| 50 \| 5.9259 \| 16.3460 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1
Sam1995/ikea_room_designs_1719805139	Sam1995	2024-07-01T18:35:02Z	0	null	[ "region:us" ]	null	2024-07-01T18:35:02Z	Entry not found
HappyMark/KidGokuJP	HappyMark	2024-07-02T12:49:47Z	0	null	[ "license:openrail", "region:us" ]	null	2024-07-01T18:35:28Z	--- license: openrail ---
ishanrajith/SG	ishanrajith	2024-07-01T18:39:08Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-07-01T18:39:08Z	--- license: apache-2.0 ---
Makkoen/whisper-large-cit-synth-do015-wd0-lr3e-06-600	Makkoen	2024-07-01T19:15:06Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2024-07-01T18:39:17Z	Entry not found

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