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RymHrizi/lora_Llema38b | RymHrizi | 2024-07-02T11:41:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:32:03Z | ---
base_model: unsloth/llama-3-8b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** RymHrizi
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-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)
|
mmolony/q-Taxi-v3 | mmolony | 2024-07-01T10:36:36Z | 0 | 0 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | reinforcement-learning | 2024-07-01T10:32:41Z | ---
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: 7.56 +/- 2.71
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="mmolony/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"])
```
|
styalai/XT-test-fineweb-0.1 | styalai | 2024-07-02T12:34:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"pytorch_model_hub_mixin",
"model_hub_mixin",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:33:09Z | ---
tags:
- pytorch_model_hub_mixin
- model_hub_mixin
---
This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
- Library: [More Information Needed]
- Docs: [More Information Needed] |
valerielucro/mistral_gsm8k_sft_and_dpo_4_beta_4 | valerielucro | 2024-07-01T10:34:21Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:34:14Z | ---
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.
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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]
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|
valerielucro/mistral_gsm8k_sft_and_dpo_4_beta_3 | valerielucro | 2024-07-01T10:35:18Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:35:11Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
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## How to Get Started with the Model
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[More Information Needed]
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[More Information Needed]
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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]
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|
acl-srw-2024/SeaLLM-7B-v2.5-unsloth-sft-epoch-3-gptq-2bit | acl-srw-2024 | 2024-07-01T10:39:58Z | 0 | 0 | transformers | [
"transformers",
"gemma",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"2-bit",
"gptq",
"region:us"
] | text-generation | 2024-07-01T10:36:11Z | Entry not found |
Aki1608/owlvit-base-patch32_FT_cppe5 | Aki1608 | 2024-07-02T12:29:16Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"owlvit",
"zero-shot-object-detection",
"endpoints_compatible",
"region:us"
] | zero-shot-object-detection | 2024-07-01T10:39:48Z | Entry not found |
igorktech/nllb-spa | igorktech | 2024-07-01T10:40:00Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:39:59Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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<!-- 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.
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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[More Information Needed]
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- **Hardware Type:** [More Information Needed]
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KiriteeGak/testing-model | KiriteeGak | 2024-07-01T10:40:00Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:40:00Z | Entry not found |
kuljeet98/inf2-bert | kuljeet98 | 2024-07-01T10:45:15Z | 0 | 0 | transformers | [
"transformers",
"bert",
"feature-extraction",
"endpoints_compatible",
"text-embeddings-inference",
"region:us"
] | feature-extraction | 2024-07-01T10:40:05Z | Entry not found |
valerielucro/mistral_gsm8k_sft_and_dpo_4_beta_6 | valerielucro | 2024-07-01T10:40:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:40:25Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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<!-- 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.
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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
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[More Information Needed]
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|
JiaxinGe/llama3_bbh_data_anthropic_dataset_transformed_dyck_1000 | JiaxinGe | 2024-07-01T10:41:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:41:43Z | ---
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
base_model: unsloth/llama-3-8b-bnb-4bit
---
# Uploaded model
- **Developed by:** JiaxinGe
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-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)
|
avkr2502/chat_vr_finetuned | avkr2502 | 2024-07-01T10:42:18Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:42:18Z | Entry not found |
valerielucro/mistral_gsm8k_sft_and_dpo_4_beta_5 | valerielucro | 2024-07-01T10:43:01Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:42:53Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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|
chw5/image | chw5 | 2024-07-01T10:44:09Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:44:09Z | Entry not found |
CatBarks/t5-lora-squad_model10 | CatBarks | 2024-07-01T10:46:02Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:45:58Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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CatBarks/t5-lora-squad_tokenizer10 | CatBarks | 2024-07-01T10:46:03Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:46:02Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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## Model Details
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syedmuhammad/Checkpoints | syedmuhammad | 2024-07-01T10:47:42Z | 0 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:google-t5/t5-small",
"license:apache-2.0",
"region:us"
] | null | 2024-07-01T10:47:37Z | ---
base_model: google-t5/t5-small
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: Checkpoints
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. -->
# Checkpoints
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- 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: 100
### Training results
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.3.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.2 |
vedanthire/hindi_gpt2 | vedanthire | 2024-07-01T11:02:14Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:gpt2",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T10:48:57Z | ---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: hindi_gpt2
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. -->
# hindi_gpt2
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
### Training results
### Framework versions
- Transformers 4.42.1
- Pytorch 1.13.0a0+08820cb
- Datasets 2.20.0
- Tokenizers 0.19.1
|
Makkoen/whisper-large-cit-synth-do0.15-wd0-lr1e-06-1000 | Makkoen | 2024-07-01T12:54:59Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"en",
"base_model:openai/whisper-large-v3",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-01T10:48:58Z | ---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./whisper-large-cit-synth-do0.15-wd0-lr1e-06-mask-1000
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. -->
# ./whisper-large-cit-synth-do0.15-wd0-lr1e-06-mask-1000
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3877
- Wer: 24.9123
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 300
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.0947 | 0.3556 | 20 | 0.8311 | 36.7251 |
| 0.8896 | 0.7111 | 40 | 0.7202 | 34.7368 |
| 0.8418 | 1.0667 | 60 | 0.6216 | 32.0078 |
| 0.6567 | 1.4222 | 80 | 0.5254 | 30.7212 |
| 0.5491 | 1.7778 | 100 | 0.4690 | 27.6803 |
| 0.5497 | 2.1333 | 120 | 0.4368 | 26.6667 |
| 0.4875 | 2.4889 | 140 | 0.4211 | 25.7310 |
| 0.4721 | 2.8444 | 160 | 0.4124 | 25.3801 |
| 0.46 | 3.2 | 180 | 0.4026 | 25.3801 |
| 0.4342 | 3.5556 | 200 | 0.3960 | 24.9513 |
| 0.4248 | 3.9111 | 220 | 0.3945 | 24.8733 |
| 0.4249 | 4.2667 | 240 | 0.3916 | 24.9123 |
| 0.4192 | 4.6222 | 260 | 0.3899 | 24.7953 |
| 0.3823 | 4.9778 | 280 | 0.3884 | 24.6004 |
| 0.4176 | 5.3333 | 300 | 0.3877 | 24.9123 |
### Framework versions
- Transformers 4.42.3
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
|
pt-sk/knowledge_distillation | pt-sk | 2024-07-01T10:49:36Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T10:49:19Z | ---
license: mit
---
|
arnab-biswas11/test1 | arnab-biswas11 | 2024-07-01T10:50:35Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-07-01T10:50:35Z | ---
license: apache-2.0
---
|
valerielucro/mistral_gsm8k_sft_and_dpo_4_beta_2 | valerielucro | 2024-07-01T10:50:48Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:50:42Z | ---
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]
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<!-- 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
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[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]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
## Model Card Contact
[More Information Needed]
|
jdmccaffrey/custom_pubmed_model | jdmccaffrey | 2024-07-01T10:54:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text2text-generation | 2024-07-01T10:52:41Z | Entry not found |
jonaskoenig/LLama-3-8b-instruct-codesmells4epoch | jonaskoenig | 2024-07-01T18:58:19Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"llama",
"text-generation",
"autotrain",
"text-generation-inference",
"peft",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T10:54:29Z | ---
license: other
library_name: transformers
tags:
- autotrain
- text-generation-inference
- text-generation
- peft
base_model: meta-llama/Meta-Llama-3-8B-Instruct
widget:
- messages:
- role: user
content: What is your favorite condiment?
---
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
``` |
hemanthkotaprolu/test_trainer | hemanthkotaprolu | 2024-07-01T10:55:32Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:55:32Z | Entry not found |
phyumonthant/llm-rag-project | phyumonthant | 2024-07-01T10:55:48Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:55:48Z | Entry not found |
Slayer247o/face | Slayer247o | 2024-07-01T10:55:51Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:55:51Z | Entry not found |
arnab-biswas11/test2 | arnab-biswas11 | 2024-07-01T11:11:08Z | 0 | 0 | null | [
"safetensors",
"license:mit",
"region:us"
] | null | 2024-07-01T10:58:26Z | ---
license: mit
---
|
Abhinay45/sml-assignment | Abhinay45 | 2024-07-01T11:00:43Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:00:43Z | Entry not found |
XxLOLxX/goofy_lora | XxLOLxX | 2024-07-01T11:07:49Z | 0 | 0 | null | [
"tensorboard",
"region:us"
] | null | 2024-07-01T11:01:21Z | Entry not found |
davepro777/AGENT_001 | davepro777 | 2024-07-01T11:06:42Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T11:06:42Z | ---
license: mit
---
|
Aung2024/gptj-qqa-model_v2 | Aung2024 | 2024-07-01T11:08:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T11:07:48Z | ---
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
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[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
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#### 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] |
whizzzzkid/whizzzzkid_368_6 | whizzzzkid | 2024-07-01T11:09:08Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:08:46Z | Entry not found |
whizzzzkid/whizzzzkid_369_1 | whizzzzkid | 2024-07-01T11:10:12Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:09:47Z | Entry not found |
whizzzzkid/whizzzzkid_370_4 | whizzzzkid | 2024-07-01T11:11:16Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:10:58Z | Entry not found |
acl-srw-2024/SeaLLM-7B-v2.5-unsloth-sft-epoch-3-gptq-3bit | acl-srw-2024 | 2024-07-01T11:15:47Z | 0 | 0 | transformers | [
"transformers",
"gemma",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"3-bit",
"gptq",
"region:us"
] | text-generation | 2024-07-01T11:11:12Z | Entry not found |
ppxin321/HolmesVAD-7B | ppxin321 | 2024-07-01T13:48:01Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"llava",
"text-generation",
"license:llama2",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:11:32Z | ---
license: llama2
---
|
whizzzzkid/whizzzzkid_371_2 | whizzzzkid | 2024-07-01T11:12:21Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:11:59Z | Entry not found |
Yumese/temp | Yumese | 2024-07-01T11:27:12Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:12:38Z | Entry not found |
asuleyman/ImageTemp | asuleyman | 2024-07-02T14:27:06Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:12:54Z | Entry not found |
whizzzzkid/whizzzzkid_372_5 | whizzzzkid | 2024-07-01T11:13:29Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:13:10Z | Entry not found |
ayush7/CBSE_Test_Science_10_v0.1 | ayush7 | 2024-07-01T15:12:33Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"custom_code",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:14:45Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
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[More Information Needed]
## Model Card Contact
[More Information Needed] |
tgrhn/whisper-large-v2-tr-cv17-3 | tgrhn | 2024-07-01T18:48:16Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"whisper-event",
"generated_from_trainer",
"tr",
"dataset:mozilla-foundation/common_voice_17",
"base_model:openai/whisper-large-v2",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-01T11:15:31Z | ---
language:
- tr
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17
model-index:
- name: 'Whisper Large v2 TR '
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. -->
# Whisper Large v2 TR
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2155
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 363 | 0.1522 |
| 0.3982 | 2.0 | 726 | 0.1484 |
| 0.0674 | 3.0 | 1089 | 0.1564 |
| 0.0674 | 4.0 | 1452 | 0.1703 |
| 0.0317 | 5.0 | 1815 | 0.1946 |
| 0.0122 | 6.0 | 2178 | 0.2155 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|
ndfkawnid/whisper-large-id | ndfkawnid | 2024-07-01T11:16:05Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:16:05Z | Entry not found |
SeyedHosseini360/my_awesome_asr_mind_model | SeyedHosseini360 | 2024-07-01T11:16:28Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:16:28Z | Entry not found |
Ksgk-fy/phillipine_customer_cognitio_v1.1_Maria-self-recognition | Ksgk-fy | 2024-07-01T17:19:36Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2024-07-01T11:17:04Z | Entry not found |
Zazalam/Me | Zazalam | 2024-07-01T11:17:31Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T11:17:31Z | ---
license: mit
---
|
Nandyala12/NeuralPipe-7B-slerp | Nandyala12 | 2024-07-01T11:21:27Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"OpenPipe/mistral-ft-optimized-1218",
"mlabonne/NeuralHermes-2.5-Mistral-7B",
"base_model:OpenPipe/mistral-ft-optimized-1218",
"base_model:mlabonne/NeuralHermes-2.5-Mistral-7B",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T11:17:51Z | ---
base_model:
- OpenPipe/mistral-ft-optimized-1218
- mlabonne/NeuralHermes-2.5-Mistral-7B
tags:
- merge
- mergekit
- lazymergekit
- OpenPipe/mistral-ft-optimized-1218
- mlabonne/NeuralHermes-2.5-Mistral-7B
---
# NeuralPipe-7B-slerp
NeuralPipe-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218)
* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
## 🧩 Configuration
```yaml
slices:
- sources:
- model: OpenPipe/mistral-ft-optimized-1218
layer_range: [0, 32]
- model: mlabonne/NeuralHermes-2.5-Mistral-7B
layer_range: [0, 32]
merge_method: slerp
base_model: OpenPipe/mistral-ft-optimized-1218
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Nandyala12/NeuralPipe-7B-slerp"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` |
westphal-jan/gpt2-german | westphal-jan | 2024-07-01T11:21:44Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T11:18:19Z | ---
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
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**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
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## Model Card Contact
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blitzapurva/query_intent_model | blitzapurva | 2024-07-01T11:18:26Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:18:26Z | Entry not found |
gabriele-dominici/lora-trained-xl | gabriele-dominici | 2024-07-01T11:19:49Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:19:49Z | Entry not found |
taric49/Phi-3_16k_2ep_adaptors | taric49 | 2024-07-01T11:25:20Z | 0 | 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 | 2024-07-01T11:24:52Z | ---
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:** taric49
- **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)
|
datakrems/Bloom | datakrems | 2024-07-02T09:50:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:25:50Z | ---
library_name: transformers
pipeline_tag: text-generation
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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[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
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[More Information Needed]
## Training Details
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#### Testing Data
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[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]
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ManuD/Meta-Llama-3-8B-Instruct-20-questions | ManuD | 2024-07-01T11:26:45Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:26:45Z | Entry not found |
habulaj/225811197548 | habulaj | 2024-07-01T11:28:50Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:28:48Z | Entry not found |
wiweka24/llama3-psychiatrist-v1.3B-lora | wiweka24 | 2024-07-01T11:31:33Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T11:31:21Z | ---
base_model: unsloth/llama-3-8b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** wiweka24
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-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)
|
Meziane/qwuestion_answering_T5_policy_qa | Meziane | 2024-07-01T11:36:03Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"question-answering",
"generated_from_trainer",
"base_model:google-t5/t5-small",
"license:apache-2.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | question-answering | 2024-07-01T11:31:41Z | ---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
model-index:
- name: qwuestion_answering_T5_policy_qa
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. -->
# qwuestion_answering_T5_policy_qa
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|
muhammtcelik/radikal-test | muhammtcelik | 2024-07-01T11:33:14Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T11:33:13Z | ---
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]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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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
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[More Information Needed]
## Training Details
### Training Data
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[More Information Needed]
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#### Preprocessing [optional]
[More Information Needed]
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- **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]
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#### Metrics
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[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]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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Echelon-AI/marathi-llama3 | Echelon-AI | 2024-07-01T16:54:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"dataset:Telugu-LLM-Labs/marathi_alpaca_yahma_cleaned_filtered",
"license:llama3",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T11:35:11Z | ---
license: llama3
datasets:
- Telugu-LLM-Labs/marathi_alpaca_yahma_cleaned_filtered
---
Meta llama3 8B trained on marathi alpaca cleaned for 1.5 epochs, On A100 40GB
## Model Overview
**Marathi-Llama3** is a fine-tuned version of the Llama3 model, tailored specifically for the Marathi language. This model leverages the power of the Llama3 architecture to provide accurate and nuanced responses in Marathi, opening up advanced AI capabilities to Marathi-speaking communities.
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load the model and tokenizer
model_name = "Echelon-AI/marathi-llama3"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
# Generate text
input_text = "कृपया मला मराठी भाषेत एक गोष्ट सांगा."
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
GGUF available at [GGUF](https://huggingface.co/ayan-sh003/marathi-llama3-GGUF) |
rristo/w2v-bert-2.0-err2020 | rristo | 2024-07-01T11:35:42Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T11:35:42Z | ---
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.
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<!-- 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
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[More Information Needed]
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<!-- 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
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[More Information Needed]
### Training Procedure
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#### Preprocessing [optional]
[More Information Needed]
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#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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## 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]
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[More Information Needed]
#### Hardware
[More Information Needed]
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[More Information Needed]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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[More Information Needed]
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[More Information Needed]
## Glossary [optional]
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[More Information Needed]
## Model Card Contact
[More Information Needed] |
multimodalart/replicate-loras-to-huggingface | multimodalart | 2024-07-01T11:42:46Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T11:36:48Z | ---
license: mit
---
## Import Replicate trained LoRAs to Hugging Face
[Jupyter Notebook](https://huggingface.co/multimodalart/replicate-loras-to-huggingface/blob/main/Import_Replicate_SDXL_LoRA_to_Hugging_Face_🤗.ipynb)
[Google Colab](https://colab.research.google.com/#fileId=https%3A//huggingface.co/multimodalart/replicate-loras-to-huggingface/blob/main/Import_Replicate_SDXL_LoRA_to_Hugging_Face_🤗.ipynb) |
habulaj/2661226268 | habulaj | 2024-07-01T11:37:24Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:37:22Z | Entry not found |
bilgingunes23/deneme | bilgingunes23 | 2024-07-01T11:39:04Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T11:37:53Z | ---
license: mit
---
|
manbeast3b/ZZZZZZZZdriver120 | manbeast3b | 2024-07-01T11:42:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:40:07Z | Entry not found |
habulaj/11930793914 | habulaj | 2024-07-01T11:42:19Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:42:18Z | Entry not found |
kksaud/modelss | kksaud | 2024-07-01T11:42:20Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:42:20Z | Entry not found |
muhammtcelik/radikal-test-gpt2 | muhammtcelik | 2024-07-01T11:42:31Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T11:42:30Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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<!-- 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
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[More Information Needed]
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[More Information Needed]
### Out-of-Scope Use
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[More Information Needed]
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<!-- 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. -->
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## Evaluation
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### Testing Data, Factors & Metrics
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## Environmental Impact
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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]
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muhammtcelik/radikal-test-redrussian | muhammtcelik | 2024-07-01T11:43:13Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T11:43:12Z | ---
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.
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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AUEB-NLP/gr-nlp-toolkit | AUEB-NLP | 2024-07-01T11:43:24Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:43:24Z | Entry not found |
oliglan/CDR | oliglan | 2024-07-01T11:43:48Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:43:48Z | Entry not found |
fxmeng/PiSSA-gemma-2-27b-r128-5iter | fxmeng | 2024-07-01T11:54:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T11:47:43Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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zaanind/aya-101 | zaanind | 2024-07-01T12:33:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mt5",
"text2text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | text2text-generation | 2024-07-01T11:47:57Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
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<!-- Provide the basic links for the model. -->
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[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
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[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. -->
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#### Metrics
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[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]
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[More Information Needed]
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bekirbakar/whisper-tiny-hi | bekirbakar | 2024-07-01T11:48:37Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:48:37Z | Entry not found |
whizzzzkid/whizzzzkid_373_3 | whizzzzkid | 2024-07-01T11:49:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:49:05Z | Entry not found |
whizzzzkid/whizzzzkid_374_7 | whizzzzkid | 2024-07-01T11:50:29Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T11:50:11Z | Entry not found |
habulaj/10864483541 | habulaj | 2024-07-01T11:50:34Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:50:27Z | Entry not found |
mhmdzrkt34/UAASSISTANT | mhmdzrkt34 | 2024-07-01T11:50:30Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:50:29Z | Entry not found |
ModelCloud/gemma-2-9b-it-gptq-4bit | ModelCloud | 2024-07-02T19:02:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"gptq",
"region:us"
] | text-generation | 2024-07-01T11:50:50Z | Quantized using [GPTQModel v0.9.2](https://github.com/ModelCloud/GPTQModel)
- **bits**: 4
- **group_size**: 128
- **desc_act**: false
- **static_groups**: false
- **sym**: true
- **lm_head**: false
- **damp_percent**: 0.01
- **true_sequential**: true
- **model_name_or_path**:
- **model_file_base_name**: model
- **quant_method**: gptq
- **checkpoint_format**: gptq
- **meta**:
- **quantizer**: gptqmodel:0.9.2
|
mlx-community/Llama-3-Swallow-70B-Instruct-v0.1-4bit | mlx-community | 2024-07-01T14:09:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mlx",
"conversational",
"en",
"ja",
"license:llama3",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T11:51:36Z | ---
language:
- en
- ja
license: llama3
library_name: transformers
tags:
- mlx
pipeline_tag: text-generation
model_type: llama
---
# mlx-community/Llama-3-Swallow-70B-Instruct-v0.1-4bit
The Model [mlx-community/Llama-3-Swallow-70B-Instruct-v0.1-4bit](https://huggingface.co/mlx-community/Llama-3-Swallow-70B-Instruct-v0.1-4bit) was converted to MLX format from [tokyotech-llm/Llama-3-Swallow-70B-Instruct-v0.1](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-70B-Instruct-v0.1) using mlx-lm version **0.13.1**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Llama-3-Swallow-70B-Instruct-v0.1-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```
|
Totsukawaii/SDXLloras | Totsukawaii | 2024-07-01T11:53:31Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:52:15Z | Entry not found |
fadhfaiz/image_classification | fadhfaiz | 2024-07-01T11:56:43Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"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 | 2024-07-01T11:52:27Z | ---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_classification
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: 0.50625
---
<!-- 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. -->
# image_classification
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: 1.4268
- Accuracy: 0.5062
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 40 | 1.8704 | 0.4062 |
| No log | 2.0 | 80 | 1.6122 | 0.3625 |
| No log | 3.0 | 120 | 1.4724 | 0.4437 |
| No log | 4.0 | 160 | 1.4352 | 0.5312 |
| No log | 5.0 | 200 | 1.4154 | 0.4375 |
| No log | 6.0 | 240 | 1.3782 | 0.5312 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|
ericsonwillians/Pixtral-7B-Instruct-v0.1 | ericsonwillians | 2024-07-01T11:53:36Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T11:53:36Z | ---
license: mit
---
|
LinxuanPastel/masquad | LinxuanPastel | 2024-07-01T13:20:50Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T11:55:53Z | Entry not found |
richardkelly/Qwen-Qwen1.5-0.5B-1719835031 | richardkelly | 2024-07-01T11:57:17Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | 2024-07-01T11:57:12Z | ---
library_name: peft
base_model: Qwen/Qwen1.5-0.5B
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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- **Developed by:** [More Information Needed]
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## 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. -->
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[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
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#### Speeds, Sizes, Times [optional]
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#### Testing Data
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<!-- 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]
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## Technical Specifications [optional]
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[More Information Needed]
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### Framework versions
- PEFT 0.11.1 |
Grace66/detectron2-image-detection | Grace66 | 2024-07-01T11:59:05Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T11:59:05Z | ---
license: mit
---
|
kevin009/mistraljorden | kevin009 | 2024-07-01T13:45:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T11:59:26Z | ---
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.
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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
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saofund/marrywise-7b-lora | saofund | 2024-07-01T12:00:12Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-07-01T12:00:12Z | 
<!-- <img src="assets/这个男人能嫁吗.jpg" width="900" alt="# MarryWise"> -->
<!-- [](https://github.com/saofund/marrywise-llm/stargazers) -->
[](LICENSE)
[](https://github.com/saofund/marrywise-llm/commits/main)
[](https://modelscope.cn/models/qwen/Qwen2-7B)
[](https://huggingface.co/saofund/marrywise-7b-lora)
[](https://x.com/976582772Wyt)
\[ English | [中文](README_zh.md) \]
<!-- **MarryWise: AI-Driven Matchmaking Analysis Tool** -->
| [](https://xn--ciqpnj1l70hxw9az0oyqy.com/) | [](https://can-he-marry.com/) |
|---|---|
| [](https://can-he-marry.com/) | [](https://can-he-marry.com/) |
## Features
- **AI Matchmaking Analyst**: Utilizing advanced AI technology to automatically analyze behavior and speech patterns during dates, revealing hidden motives and true personality traits.
- **AI Fake Matchmaker Detector**: Helps users identify potential deceitful behavior during the dating process, ensuring the authenticity and reliability of partners.
## Main Analysis Dimensions
- **Personality Authenticity**: Assessing the true character of a potential partner through behavior and speech analysis.
- **Actual Motives**: Revealing the real intentions behind a suitor's actions to prevent being deceived by appearances.
- **Personal Achievements**: Evaluating a suitor's personal achievements and capabilities to ensure their descriptions match reality.
## Fine-tuning Data Example
Fine-tuned using [Qwen2-7B](https://qwen.readthedocs.io/en/latest/getting_started/quickstart.html), example of fine-tuning data (coming soon).
| Input (Conditions) | Output (After analysis, large model conversion) |
| ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| 1. 32 years old, 178cm <br> 2. Collects rent, annual income of 15104 <br> 3. 6 houses, one car <br> 4. Loves cleanliness, cooking, wife, parents divorced and lives with mother, mother is gentle. | 🔍 Hidden Secrets: The truth he doesn't want you to know <br> In the dazzling matchmaking market, everyone tries to show their best side. But beware of those unspoken secrets, they could be stumbling blocks on your path to happiness. <br> 🍳 The weight mystery behind cooking <br> He claims to be a cooking master, living an easy and comfortable life. But numbers don't lie: the undisclosed weight may hint at an unhealthy lifestyle. Don't overlook long-term health risks while enjoying the delicacies. <br> 💰 Questions about property origin <br> Six properties, one car—seemingly solid financial foundation. But where do these assets come from? Being a demolition household might signify luck, or it could indicate a lack of ambition. <br> 👨👩👦 Complexity of family relationships <br> He praises his mother's gentleness and easy-going nature, but does it mean he cannot be independent? The mother-son relationship in a single-parent family may be more complex than it appears, potentially affecting future family harmony. <br> 💍 The "loving wife" label trap <br> "Loving wife" sounds perfect, but beware it could be a psychological tactic. Don't be easily fooled by this label without delving into his true intentions. <br> 🔍 Deep Dive: What are the real motives? <br> He understands women, but why is he still single? There might be hidden secrets under his perfect exterior. Uncover the veil and see his true motives before making a decision. |
## Local Setup
##### Detailed Steps:
```shell
# Download Qwen2-7B-Instruct model: https://modelscope.cn/models/qwen/Qwen2-7B/files
git lfs install
git clone https://www.modelscope.cn/qwen/Qwen2-7B.git
# Download lora weights
# Install LLaMA-Factory
git clone --depth 1 https://github.com/hiyouga/LLaMA-Factory.git
cd LLaMA-Factory
pip install -e ".[torch,metrics]" # Install dependencies, follow the official instructions
# Use LLaMA-Factory to merge lora weights
# Requires GPU, approximately 12G VRAM usage
llamafactory-cli export \
--model_name_or_path Qwen2-7B-Instruct \ # The just downloaded Qwen2-7B weights
--adapter_name_or_path output_qwen\ # Path to lora weights
--template qwen \ # Default
--finetuning_type lora \ # Default
--export_dir lora_full_param_model \ # Output path for full weights
--export_size 2 \ # Default
--export_legacy_format False # Default
# Official Qwen2 inference test script, replace the weight path with the merged path
python cli_demo.py -c path_to_merged_weights # Approximately 15G VRAM
# Note: Due to the "style" characteristics of lora fine-tuning, specific prompt words need to be added at the beginning of the question:
# Your role is a matchmaking condition analyst, specializing in identifying the "hidden" conditions not mentioned by the male party, analyzing the "secrets not mentioned" in matchmaking. xxxx (followed by specific conditions)
```
##### Local CLI Result:
<img src="assets/sft_demo.png" width="500" alt="CLI Result">
#### Contact the Author
For dataset acquisition, models, algorithms, technical exchanges, and collaborative development, feel free to add the author's WeChat.
| Author's WeChat QR Code | sáo Fund Sponsorship |
|---|---|
|  |  |
| For dataset acquisition, models, algorithms, technical exchanges, and collaborative development, feel free to add the author's WeChat. | Sponsored by sáo Fund, thank you. |
|
richardkelly/Qwen-Qwen1.5-1.8B-1719835275 | richardkelly | 2024-07-01T12:01:21Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | 2024-07-01T12:01:15Z | ---
library_name: peft
base_model: Qwen/Qwen1.5-1.8B
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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[More Information Needed]
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<!-- 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
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[More Information Needed]
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<!-- 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]
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- PEFT 0.11.1 |
Meziane/qwuestion_answering_T5_policy_qa_ | Meziane | 2024-07-01T12:03:28Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"question-answering",
"generated_from_trainer",
"base_model:google-t5/t5-small",
"license:apache-2.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | question-answering | 2024-07-01T12:01:17Z | ---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
model-index:
- name: qwuestion_answering_T5_policy_qa_
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. -->
# qwuestion_answering_T5_policy_qa_
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|
habulaj/5426141662 | habulaj | 2024-07-01T12:02:04Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T12:01:53Z | Entry not found |
itay-nakash/model_42d9b05c5c_sweep_restful-bird-1146 | itay-nakash | 2024-07-01T12:04:49Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T12:04:49Z | Entry not found |
richardkelly/google-gemma-2b-1719835499 | richardkelly | 2024-07-01T12:05:00Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T12:05:00Z | Entry not found |
habulaj/11880893417 | habulaj | 2024-07-01T12:05:57Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T12:05:29Z | Entry not found |
aroraaman/img-tensor | aroraaman | 2024-07-01T12:26:52Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-07-01T12:05:54Z | ---
license: apache-2.0
---
|
NikshepShetty/Florence-2-DOCCI-FT | NikshepShetty | 2024-07-01T18:01:59Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T12:06:00Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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[More Information Needed]
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[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
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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[More Information Needed]
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[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]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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chainup244/Qwen-Qwen1.5-0.5B-1719835561 | chainup244 | 2024-07-01T12:06:35Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T12:06:03Z | ---
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]
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<!-- Provide the basic links for the model. -->
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## How to Get Started with the Model
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## Training Details
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baxtos/bigirnik07-35 | baxtos | 2024-07-01T12:08:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T12:06:21Z | Entry not found |
ellie3000/Imageclassifier2 | ellie3000 | 2024-07-01T12:08:25Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T12:08:25Z | Entry not found |
Beijuka/wav2vec2_xls_r_300m_NCHLT_Speech_corpus_Xhosa_20hr_v1 | Beijuka | 2024-07-03T00:08:57Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:facebook/wav2vec2-xls-r-300m",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-01T12:08:58Z | ---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2_xls_r_300m_NCHLT_Speech_corpus_Xhosa_20hr_v1
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/ndw7wq2v)
# wav2vec2_xls_r_300m_NCHLT_Speech_corpus_Xhosa_20hr_v1
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2579
- Wer: 0.4319
- Cer: 0.0462
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 1.843 | 1.0 | 576 | 0.5899 | 0.9703 | 0.1934 |
| 0.4473 | 2.0 | 1152 | 0.3200 | 0.6919 | 0.1017 |
| 0.3477 | 3.0 | 1728 | 0.2716 | 0.9294 | 0.1142 |
| 0.2842 | 4.0 | 2304 | 0.2402 | 0.8098 | 0.0955 |
| 0.2647 | 5.0 | 2880 | 0.2351 | 0.5797 | 0.0684 |
| 0.2326 | 6.0 | 3456 | 0.2310 | 0.6368 | 0.0771 |
| 0.201 | 7.0 | 4032 | 0.2307 | 0.5743 | 0.0676 |
| 0.1843 | 8.0 | 4608 | 0.2214 | 0.7284 | 0.0800 |
| 0.1737 | 9.0 | 5184 | 0.2139 | 0.6412 | 0.0682 |
| 0.1551 | 10.0 | 5760 | 0.2152 | 0.6807 | 0.0757 |
| 0.144 | 11.0 | 6336 | 0.2171 | 0.6997 | 0.0750 |
| 0.1272 | 12.0 | 6912 | 0.2190 | 0.6652 | 0.0694 |
| 0.1154 | 13.0 | 7488 | 0.2192 | 0.5226 | 0.0591 |
| 0.1037 | 14.0 | 8064 | 0.2190 | 0.5706 | 0.0580 |
| 0.0944 | 15.0 | 8640 | 0.2141 | 0.5351 | 0.0553 |
| 0.1022 | 16.0 | 9216 | 0.2244 | 0.5041 | 0.0546 |
| 0.091 | 17.0 | 9792 | 0.2124 | 0.5020 | 0.0518 |
| 0.0862 | 18.0 | 10368 | 0.2112 | 0.4855 | 0.0502 |
| 0.0781 | 19.0 | 10944 | 0.2298 | 0.5595 | 0.0577 |
| 0.0775 | 20.0 | 11520 | 0.2177 | 0.4780 | 0.0523 |
| 0.0656 | 21.0 | 12096 | 0.2032 | 0.4463 | 0.0451 |
| 0.0633 | 22.0 | 12672 | 0.2062 | 0.4490 | 0.0484 |
| 0.0695 | 23.0 | 13248 | 0.2035 | 0.4270 | 0.0466 |
| 0.0585 | 24.0 | 13824 | 0.2134 | 0.5848 | 0.0571 |
| 0.0559 | 25.0 | 14400 | 0.2155 | 0.4591 | 0.0495 |
| 0.0474 | 26.0 | 14976 | 0.2092 | 0.4490 | 0.0475 |
| 0.0509 | 27.0 | 15552 | 0.2106 | 0.4345 | 0.0472 |
| 0.0453 | 28.0 | 16128 | 0.2093 | 0.4159 | 0.0425 |
| 0.0472 | 29.0 | 16704 | 0.2102 | 0.4530 | 0.0473 |
| 0.0404 | 30.0 | 17280 | 0.2091 | 0.4017 | 0.0417 |
| 0.0451 | 31.0 | 17856 | 0.2122 | 0.3885 | 0.0405 |
| 0.0383 | 32.0 | 18432 | 0.2151 | 0.4027 | 0.0431 |
| 0.038 | 33.0 | 19008 | 0.2189 | 0.3959 | 0.0406 |
| 0.0365 | 34.0 | 19584 | 0.2067 | 0.4527 | 0.0478 |
| 0.0375 | 35.0 | 20160 | 0.2099 | 0.3723 | 0.0384 |
| 0.0335 | 36.0 | 20736 | 0.2074 | 0.4017 | 0.0419 |
| 0.0358 | 37.0 | 21312 | 0.1967 | 0.4196 | 0.0440 |
| 0.0408 | 38.0 | 21888 | 0.2070 | 0.5189 | 0.0507 |
| 0.0299 | 39.0 | 22464 | 0.2041 | 0.4297 | 0.0415 |
| 0.0321 | 40.0 | 23040 | 0.2188 | 0.4024 | 0.0410 |
| 0.0314 | 41.0 | 23616 | 0.2033 | 0.3706 | 0.0388 |
| 0.0328 | 42.0 | 24192 | 0.2097 | 0.4047 | 0.0466 |
| 0.0289 | 43.0 | 24768 | 0.2118 | 0.3855 | 0.0396 |
| 0.0306 | 44.0 | 25344 | 0.2092 | 0.4486 | 0.0433 |
| 0.0274 | 45.0 | 25920 | 0.2000 | 0.3946 | 0.0394 |
| 0.0235 | 46.0 | 26496 | 0.2011 | 0.3368 | 0.0347 |
| 0.0222 | 47.0 | 27072 | 0.1990 | 0.3375 | 0.0344 |
| 0.0197 | 48.0 | 27648 | 0.2052 | 0.3446 | 0.0355 |
| 0.0218 | 49.0 | 28224 | 0.2157 | 0.3858 | 0.0415 |
| 0.0212 | 50.0 | 28800 | 0.2096 | 0.3716 | 0.0375 |
| 0.0197 | 51.0 | 29376 | 0.2140 | 0.3736 | 0.0366 |
| 0.0205 | 52.0 | 29952 | 0.2054 | 0.3574 | 0.0376 |
| 0.0192 | 53.0 | 30528 | 0.1993 | 0.3402 | 0.0341 |
| 0.0173 | 54.0 | 31104 | 0.1997 | 0.3493 | 0.0366 |
| 0.0181 | 55.0 | 31680 | 0.2038 | 0.3318 | 0.0349 |
| 0.0181 | 56.0 | 32256 | 0.2113 | 0.3375 | 0.0342 |
| 0.0141 | 57.0 | 32832 | 0.2112 | 0.3436 | 0.0366 |
| 0.0147 | 58.0 | 33408 | 0.2090 | 0.4155 | 0.0409 |
| 0.0147 | 59.0 | 33984 | 0.2120 | 0.3970 | 0.0402 |
| 0.0152 | 60.0 | 34560 | 0.2072 | 0.4017 | 0.0411 |
| 0.0198 | 61.0 | 35136 | 0.2167 | 0.5334 | 0.0495 |
| 0.0141 | 62.0 | 35712 | 0.2092 | 0.5318 | 0.0478 |
| 0.0137 | 63.0 | 36288 | 0.2063 | 0.6223 | 0.0549 |
| 0.0147 | 64.0 | 36864 | 0.2135 | 0.5632 | 0.0488 |
| 0.01 | 65.0 | 37440 | 0.2140 | 0.4943 | 0.0453 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
|
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