librarian-bots/model_cards_with_metadata_test

modelId stringlengths 5 122	author stringlengths 2 42	last_modified unknown	likes int64 0 10.9k	library_name stringclasses 243 values	tags sequencelengths 1 2.16k	pipeline_tag stringclasses 48 values	createdAt unknown	card stringlengths 1 901k
Tinuva/MidkemiaAnimeTV	Tinuva	"2024-06-16T17:54:42Z"	0	null	[ "license:creativeml-openrail-m", "region:us" ]	null	"2024-06-16T17:44:04Z"	--- license: creativeml-openrail-m ---
fruk19/whisper-thai-north	fruk19	"2024-06-16T17:48:09Z"	0	null	[ "region:us" ]	null	"2024-06-16T17:48:09Z"	Entry not found
clxudiajazmin/ClaudiaSoria_TFM_V4	clxudiajazmin	"2024-06-17T12:00:17Z"	0	transformers	[ "transformers", "safetensors", "t5", "text2text-generation", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text2text-generation	"2024-06-16T17:49:00Z"	Entry not found
lhbit20010120/without_vg_refcoco_model	lhbit20010120	"2024-06-16T17:50:43Z"	0	null	[ "region:us" ]	null	"2024-06-16T17:50:43Z"	Entry not found
fruk19/thainorthmodel	fruk19	"2024-06-16T18:13:42Z"	0	transformers	[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	"2024-06-16T18:00:51Z"	Entry not found
menglc/deepstack-l-vicuna-7b	menglc	"2024-06-17T03:18:58Z"	0	transformers	[ "transformers", "safetensors", "deepstack_llama", "text-generation", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	"2024-06-16T18:03:55Z"	--- license: apache-2.0 ---
samannar/ddduva	samannar	"2024-06-16T18:03:57Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T18:03:57Z"	--- license: openrail ---
Jareen/tesing	Jareen	"2024-06-16T18:07:38Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:07:38Z"	Entry not found
SeoulStreamingStation/KLM4	SeoulStreamingStation	"2024-06-16T19:14:36Z"	5	null	[ "license:other", "region:us" ]	null	"2024-06-16T18:12:13Z"	--- license: other license_name: sss license_link: LICENSE ---
moschouChry/chronos-t5-finetuned_small_1-Patient0-fine-tuned_20240616_205512	moschouChry	"2024-06-16T18:14:56Z"	0	transformers	[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text2text-generation	"2024-06-16T18:14:39Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
SilvioLima/absa_treinamento_2	SilvioLima	"2024-06-16T19:05:14Z"	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text-generation	"2024-06-16T18:15:40Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
north/llama2_DensityExperiment_filtered80-70k-exporttest	north	"2024-06-16T18:26:02Z"	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text-generation	"2024-06-16T18:17:01Z"	Entry not found
Emmanuel132/Mack_dm690s	Emmanuel132	"2024-06-16T18:19:35Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:19:34Z"	Entry not found
EugeneShally/whisper-small-nl	EugeneShally	"2024-06-17T05:27:31Z"	0	transformers	[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	"2024-06-16T18:24:57Z"	Entry not found
Mohammed-majeed/llama-3-8b-bnb-4bit-Unsloth-chunk-7-0.5-2	Mohammed-majeed	"2024-06-16T18:26:57Z"	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	"2024-06-16T18:25:56Z"	--- 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: Mohammed-majeed - 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)
bfrenan/Llama3-log-to-ttp-lora-adapters_2	bfrenan	"2024-06-16T18:29:46Z"	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:unsloth/llama-3-8b-Instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	"2024-06-16T18:29:38Z"	--- language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl base_model: unsloth/llama-3-8b-Instruct-bnb-4bit --- # Uploaded model - Developed by: bfrenan - License: apache-2.0 - Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
bfrenan/Llama3-log-to-ttp-tokenizer_2	bfrenan	"2024-06-16T18:29:48Z"	0	transformers	[ "transformers", "unsloth", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	"2024-06-16T18:29:47Z"	--- library_name: transformers tags: - unsloth --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Fawazzx/alzheimer_classification_using_resnet50_finetuned	Fawazzx	"2024-06-16T21:37:29Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:30:25Z"	# Fine-Tuning ResNet50 for Alzheimer's MRI Classification This repository contains a Jupyter Notebook for fine-tuning a ResNet50 model to classify Alzheimer's disease stages from MRI images. The notebook uses PyTorch and the dataset is loaded from the Hugging Face Datasets library. ## Table of Contents - [Introduction](#introduction) - [Dataset](#dataset) - [Model Architecture](#model-architecture) - [Setup](#setup) - [Training](#training) - [Evaluation](#evaluation) - [Usage](#usage) - [Results](#results) - [Contributing](#contributing) - [License](#license) ## Introduction This notebook fine-tunes a pre-trained ResNet50 model to classify MRI images into one of four stages of Alzheimer's disease: - Mild Demented - Moderate Demented - Non-Demented - Very Mild Demented ## Dataset The dataset used is [Falah/Alzheimer_MRI](https://huggingface.co/datasets/Falah/Alzheimer_MRI) from the Hugging Face Datasets library. It consists of MRI images categorized into the four stages of Alzheimer's disease. ## Model Architecture The model architecture is based on ResNet50. The final fully connected layer is modified to output predictions for 4 classes. ## Setup To run the notebook locally, follow these steps: 1. Clone the repository: ```bash git clone https://github.com/your_username/alzheimer_mri_classification.git cd alzheimer_mri_classification ``` 2. Install the required dependencies: ```bash pip install -r requirements.txt ``` 3. Open the notebook: ```bash jupyter notebook fine-tuning.ipynb ``` ## Training The notebook includes sections for: - Loading and preprocessing the dataset - Defining the model architecture - Setting up the training loop with a learning rate scheduler and optimizer - Training the model for a specified number of epochs - Saving the trained model weights ## Evaluation The notebook includes a section for evaluating the trained model on the validation set. It calculates and prints the validation loss and accuracy. ## Usage Once trained, the model can be saved and used for inference on new MRI images. The trained model weights are saved as alzheimer_model_resnet50.pth. ## Load the model architecture and weights ```python model = models.resnet50(weights=None) model.fc = nn.Linear(model.fc.in_features, 4) model.load_state_dict(torch.load("alzheimer_model_resnet50.pth", map_location=torch.device('cpu'))) model.eval() ``` ## Results The model achieved an accuracy of 95.9375% on the validation set. ## Contributing Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request.
seashorers/GRAGAS	seashorers	"2024-06-17T00:52:46Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T18:30:39Z"	--- license: openrail ---
hngan/cocowholebody	hngan	"2024-06-16T18:40:21Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:31:24Z"	Entry not found
SukritSNegi/Llama-2-7b-chat-new-finetune	SukritSNegi	"2024-06-22T10:47:39Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:38:43Z"	Entry not found
dtruong46me/flant5-large-lora	dtruong46me	"2024-06-16T18:41:25Z"	0	peft	[ "peft", "safetensors", "generated_from_trainer", "base_model:google/flan-t5-large", "license:apache-2.0", "region:us" ]	null	"2024-06-16T18:41:15Z"	--- license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: google/flan-t5-large metrics: - rouge model-index: - name: flant5-large-lora results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # flant5-large-lora This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6119 - Rouge1: 8.9675 - Rouge2: 0.6714 - Rougel: 8.0407 - Rougelsum: 8.3753 - Gen Len: 18.37 ## 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: 6 - eval_batch_size: 6 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rouge1 \| Rouge2 \| Rougel \| Rougelsum \| Gen Len \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\|:------:\|:------:\|:---------:\|:-------:\| \| 1.8402 \| 1.0 \| 1538 \| 0.7486 \| 8.8441 \| 0.6859 \| 7.9731 \| 8.3103 \| 19.502 \| \| 0.8152 \| 2.0 \| 3076 \| 0.6119 \| 8.9675 \| 0.6714 \| 8.0407 \| 8.3753 \| 18.37 \| ### Framework versions - PEFT 0.11.1 - Transformers 4.36.1 - Pytorch 2.1.2 - Datasets 2.20.0 - Tokenizers 0.15.2
moschouChry/chronos-t5-finetuned_small_1-Patient0-fine-tuned_20240616_205441	moschouChry	"2024-06-16T18:42:24Z"	0	transformers	[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text2text-generation	"2024-06-16T18:42:10Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
PLS442/Yoko	PLS442	"2024-06-16T18:43:49Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T18:43:02Z"	--- license: openrail ---
coco233/run	coco233	"2024-06-16T18:44:35Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:43:28Z"	Entry not found
abyesses/results	abyesses	"2024-06-16T18:43:56Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:43:56Z"	Entry not found
gamallo/translator-gl-zh	gamallo	"2024-06-16T22:16:38Z"	0	null	[ "license:mit", "region:us" ]	null	"2024-06-16T18:44:02Z"	--- license: mit --- How to translate with this model + Install [Python 3.9](https://www.python.org/downloads/release/python-390/) + ctranslate 2 + subword-nmt ```bash pip install ctranslate2~=3.20.0 ``` ```bash pip install subword-nmt ``` + tokenization with BPE: ```bash subword-nmt apply-bpe -c gl-detok10k.code < input_file.txt > input_file_bpe.txt ``` + Translating an input_text using ct2_detok-gl-zh: ```bash python3 trans_ct2.py ct2_detok-gl-zh input_file_bpe.txt >output_file_bpe.txt ``` + DeBPEar output txt: ```bash cat out_test_bpe.txt \| sed "s/@@ //g" > output_file.txt ``` Acknowledgments Thanks to Tang Waying, Zheng Jie and Wang Tianjiao for helping prepare the parallel corpora.
puipuipui/zee	puipuipui	"2024-06-16T19:12:53Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:44:14Z"	Entry not found
lucao123/h-an-m-model	lucao123	"2024-06-16T18:46:44Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:46:43Z"	Entry not found
Paco4365483/Finetune10	Paco4365483	"2024-06-16T19:02:31Z"	0	transformers	[ "transformers", "safetensors", "llava_llama", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	"2024-06-16T18:50:52Z"	Entry not found
strwbrylily/Im-Nayeon-by-strwbrylily	strwbrylily	"2024-06-16T18:55:29Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T18:54:50Z"	--- license: openrail ---
numen-tech/Llama-3-WhiteRabbitNeo-8B-v2.0-w4a16g128asym	numen-tech	"2024-06-16T19:00:17Z"	0	null	[ "arxiv:2308.13137", "license:llama3", "region:us" ]	null	"2024-06-16T18:55:34Z"	--- license: llama3 --- 4-bit [OmniQuant](https://arxiv.org/abs/2308.13137) quantized version of [Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0).
codingninja/testing	codingninja	"2024-06-16T18:55:43Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:55:43Z"	Entry not found
numen-tech/Llama-3-WhiteRabbitNeo-8B-v2.0-w3a16g40sym	numen-tech	"2024-06-16T19:00:26Z"	0	null	[ "arxiv:2308.13137", "license:llama3", "region:us" ]	null	"2024-06-16T18:56:01Z"	--- license: llama3 --- 3-bit [OmniQuant](https://arxiv.org/abs/2308.13137) quantized version of [Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0).
kaitr/opt-6.7b-lora	kaitr	"2024-06-16T18:59:00Z"	0	null	[ "region:us" ]	null	"2024-06-16T18:59:00Z"	Entry not found
AndreMitri/BERT_cls_polaridade	AndreMitri	"2024-06-16T19:05:22Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:04:20Z"	Entry not found
Danyt24/finetuning-sentiment-model-4000-samples	Danyt24	"2024-06-16T19:06:29Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:06:29Z"	Entry not found
HotDrify/thelemyAI	HotDrify	"2024-06-16T19:06:31Z"	0	null	[ "license:mit", "region:us" ]	null	"2024-06-16T19:06:31Z"	--- license: mit ---
silent666/Qwen-Qwen1.5-7B-1718564795	silent666	"2024-06-16T19:06:38Z"	0	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:Qwen/Qwen1.5-7B", "region:us" ]	null	"2024-06-16T19:06:35Z"	--- base_model: Qwen/Qwen1.5-7B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.11.1
iasjkk/MV_EC	iasjkk	"2024-06-24T09:49:07Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:07:21Z"	Entry not found
levipereira/yolov8n-trt	levipereira	"2024-06-16T19:08:44Z"	0	null	[ "license:agpl-3.0", "region:us" ]	null	"2024-06-16T19:08:43Z"	--- license: agpl-3.0 ---
Nibo4k/CantoraCreditos	Nibo4k	"2024-06-16T21:24:51Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:11:43Z"	Entry not found
Testvsls0224/test1model	Testvsls0224	"2024-06-17T01:57:50Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:11:58Z"	Entry not found
Damir4/izamodel	Damir4	"2024-06-16T19:12:05Z"	0	null	[ "license:gpl-3.0", "region:us" ]	null	"2024-06-16T19:12:05Z"	--- license: gpl-3.0 ---
vsls0224/testModel	vsls0224	"2024-06-16T19:13:10Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:13:10Z"	Entry not found
ahmedesmail16/0.50-800Train-100Test-beit-base	ahmedesmail16	"2024-06-17T00:18:58Z"	0	transformers	[ "transformers", "tensorboard", "safetensors", "beit", "image-classification", "generated_from_trainer", "base_model:microsoft/beit-base-patch16-224-pt22k-ft22k", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	"2024-06-16T19:16:41Z"	--- license: apache-2.0 base_model: microsoft/beit-base-patch16-224-pt22k-ft22k tags: - generated_from_trainer metrics: - accuracy model-index: - name: 0.50-800Train-100Test-beit-base 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. --> # 0.50-800Train-100Test-beit-base This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.7501 - Accuracy: 0.8192 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 512 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:------:\|:----:\|:---------------:\|:--------:\| \| 0.7627 \| 0.9536 \| 18 \| 0.6991 \| 0.7860 \| \| 0.3414 \| 1.9603 \| 37 \| 0.5881 \| 0.8070 \| \| 0.1402 \| 2.9669 \| 56 \| 0.5879 \| 0.8114 \| \| 0.0663 \| 3.9735 \| 75 \| 0.6249 \| 0.8175 \| \| 0.0377 \| 4.9801 \| 94 \| 0.6539 \| 0.8210 \| \| 0.0314 \| 5.9868 \| 113 \| 0.7074 \| 0.8175 \| \| 0.0189 \| 6.9934 \| 132 \| 0.7596 \| 0.8210 \| \| 0.0147 \| 8.0 \| 151 \| 0.7211 \| 0.8253 \| \| 0.0157 \| 8.9536 \| 169 \| 0.7412 \| 0.8166 \| \| 0.0095 \| 9.5364 \| 180 \| 0.7501 \| 0.8192 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.1.2 - Datasets 2.19.2 - Tokenizers 0.19.1
Rrrr3/Hhk	Rrrr3	"2024-06-16T19:18:07Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:18:07Z"	Entry not found
andreluiz1/teste	andreluiz1	"2024-06-16T19:21:34Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T19:21:34Z"	--- license: openrail ---
mjfan1999/LukeCombs2024	mjfan1999	"2024-06-16T19:32:06Z"	0	null	[ "license:unknown", "region:us" ]	null	"2024-06-16T19:22:29Z"	--- license: unknown ---
dostoewslybtw/portal_of_i	dostoewslybtw	"2024-06-16T19:24:01Z"	0	null	[ "license:apache-2.0", "region:us" ]	null	"2024-06-16T19:24:01Z"	--- license: apache-2.0 ---
moschouChry/chronos-t5-finetuned_small_1-Patient0-fine-tuned_20240616_205414	moschouChry	"2024-06-16T19:25:11Z"	0	transformers	[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text2text-generation	"2024-06-16T19:24:57Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
codingninja/openchat-7b-galbaat	codingninja	"2024-06-21T13:22:07Z"	0	null	[ "tensorboard", "safetensors", "region:us" ]	null	"2024-06-16T19:25:09Z"	Entry not found
royvdkoelen/DayZ	royvdkoelen	"2024-06-16T19:26:24Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:26:24Z"	Entry not found
matthewleechen/yolov8s_ukpatents_singleclass	matthewleechen	"2024-06-16T19:27:14Z"	0	null	[ "tensorboard", "region:us" ]	null	"2024-06-16T19:26:30Z"	Entry not found
aerainyourarea/S1Seoyeon	aerainyourarea	"2024-06-16T19:34:03Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T19:26:40Z"	--- license: openrail ---
Marco127/llamantino_hodi_requalification	Marco127	"2024-06-16T21:45:13Z"	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	"2024-06-16T19:28:21Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
JhuTheBunny999/Frey	JhuTheBunny999	"2024-06-20T09:39:04Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:31:48Z"	Entry not found
strwbrylily/Kim-Jiwoo-RUNext-by-strwbrylily	strwbrylily	"2024-06-16T19:34:11Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T19:31:51Z"	--- license: openrail ---
TheMindExpansionNetwork/m1nd3xpand3r-1024x1024-sd3-lora	TheMindExpansionNetwork	"2024-06-16T19:36:26Z"	0	null	[ "region:us" ]	null	"2024-06-16T19:36:26Z"	Entry not found
Mortello/q-FrozenLake-v1	Mortello	"2024-06-16T19:36:51Z"	0	null	[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	"2024-06-16T19:36:48Z"	--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # Q-Learning Agent playing1 FrozenLake-v1 This is a trained model of a Q-Learning agent playing FrozenLake-v1 . ## Usage ```python model = load_from_hub(repo_id="Mortello/q-FrozenLake-v1", 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"]) ```
T-ZERO/first_prototype	T-ZERO	"2024-06-16T19:44:23Z"	0	flair	[ "flair", "legal", "text-generation", "fa", "dataset:OpenGVLab/ShareGPT-4o", "license:llama3", "region:us" ]	text-generation	"2024-06-16T19:38:26Z"	--- license: llama3 datasets: - OpenGVLab/ShareGPT-4o language: - fa metrics: - character library_name: flair pipeline_tag: text-generation tags: - legal ---
IlyaGusev/saiga_llama3_70b_sft_m1_d5_abliterated_kto_m1_d2_lora	IlyaGusev	"2024-06-16T19:42:25Z"	0	null	[ "safetensors", "region:us" ]	null	"2024-06-16T19:39:29Z"	Entry not found
Mortello/q-Taxi-v3	Mortello	"2024-06-16T19:43:32Z"	0	null	[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	"2024-06-16T19:43:31Z"	--- 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: 7.54 +/- 2.74 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="Mortello/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"]) ```
kawagoshi-llm-team/test_40B	kawagoshi-llm-team	"2024-06-16T19:58:12Z"	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text-generation	"2024-06-16T19:45:39Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
menglc/deepstack-l-hd-vicuna-7b	menglc	"2024-06-17T03:08:34Z"	0	transformers	[ "transformers", "safetensors", "deepstack_llama", "text-generation", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	"2024-06-16T19:49:03Z"	--- license: apache-2.0 ---
stojchet/python-sft-r64-a16-d0.05-e3	stojchet	"2024-06-16T19:54:05Z"	0	peft	[ "peft", "safetensors", "trl", "sft", "generated_from_trainer", "dataset:generator", "base_model:deepseek-ai/deepseek-coder-1.3b-base", "license:other", "region:us" ]	null	"2024-06-16T19:53:59Z"	--- base_model: deepseek-ai/deepseek-coder-1.3b-base datasets: - generator library_name: peft license: other tags: - trl - sft - generated_from_trainer model-index: - name: python-sft-r64-a16-d0.05-e3 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/stojchets/huggingface/runs/rmvtpvu9) # python-sft-r64-a16-d0.05-e3 This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on the generator 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: 1.41e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results ### Framework versions - PEFT 0.10.0 - Transformers 4.42.0.dev0 - Pytorch 2.2.2+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1
BIFOLD-BigEarthNetv2-0/BENv2-resnet50-s1-v0.1.1	BIFOLD-BigEarthNetv2-0	"2024-06-19T14:09:01Z"	0	transformers	[ "transformers", "safetensors", "model_hub_mixin", "pytorch_model_hub_mixin", "endpoints_compatible", "region:us" ]	null	"2024-06-16T19:57:51Z"	--- tags: - model_hub_mixin - pytorch_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]
pwl15/llava-v1.5-food101	pwl15	"2024-06-17T18:52:42Z"	0	null	[ "safetensors", "region:us" ]	null	"2024-06-16T19:59:04Z"	Entry not found
kohapahm/distilhubert-finetuned-gtzan	kohapahm	"2024-06-16T20:00:38Z"	0	null	[ "region:us" ]	null	"2024-06-16T20:00:38Z"	Entry not found
CLASS-MATE/llama2-train_test	CLASS-MATE	"2024-06-17T22:40:18Z"	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	"2024-06-16T20:03:31Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
xpozryx/ponyRealisticTrainingColab	xpozryx	"2024-06-16T21:59:23Z"	0	null	[ "region:us" ]	null	"2024-06-16T20:07:59Z"	Entry not found
SkyWR/wgn	SkyWR	"2024-06-16T20:12:04Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T20:09:32Z"	--- license: openrail ---
evitalyst/ChatMe	evitalyst	"2024-06-16T20:09:57Z"	0	null	[ "license:apache-2.0", "region:us" ]	null	"2024-06-16T20:09:57Z"	--- license: apache-2.0 ---
Yuseifer/Reinforce_model-cartpole	Yuseifer	"2024-06-16T20:10:22Z"	0	null	[ "CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class", "model-index", "region:us" ]	reinforcement-learning	"2024-06-16T20:10:13Z"	--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce_model-cartpole results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: - type: mean_reward value: 467.80 +/- 96.60 name: mean_reward verified: false --- # Reinforce Agent playing CartPole-v1 This is a trained model of a Reinforce agent playing CartPole-v1 . To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
BIFOLD-BigEarthNetv2-0/BENv2-resnet101-s1-v0.1.1	BIFOLD-BigEarthNetv2-0	"2024-06-19T14:12:15Z"	0	transformers	[ "transformers", "safetensors", "model_hub_mixin", "pytorch_model_hub_mixin", "endpoints_compatible", "region:us" ]	null	"2024-06-16T20:10:41Z"	--- tags: - model_hub_mixin - pytorch_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]
sharad31/my_model	sharad31	"2024-06-16T20:12:02Z"	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	"2024-06-16T20:11:37Z"	--- 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: sharad31 - 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)
shunsso/data	shunsso	"2024-06-16T20:19:13Z"	0	null	[ "region:us" ]	null	"2024-06-16T20:19:13Z"	Entry not found
Roo89/Ru	Roo89	"2024-06-16T20:19:36Z"	0	null	[ "region:us" ]	null	"2024-06-16T20:19:36Z"	Entry not found
GalaktischeGurke/whisper-large-v3_German_merge_ratio_ch_de_0.5	GalaktischeGurke	"2024-06-16T20:19:51Z"	0	null	[ "region:us" ]	null	"2024-06-16T20:19:51Z"	Entry not found
BIFOLD-BigEarthNetv2-0/BENv2-resnet50-s2-v0.1.1	BIFOLD-BigEarthNetv2-0	"2024-06-19T14:28:11Z"	0	transformers	[ "transformers", "safetensors", "model_hub_mixin", "pytorch_model_hub_mixin", "endpoints_compatible", "region:us" ]	null	"2024-06-16T20:22:36Z"	--- tags: - model_hub_mixin - pytorch_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]
sharad31/talktoyourself	sharad31	"2024-06-16T20:29:14Z"	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	"2024-06-16T20:29:04Z"	--- 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: sharad31 - 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)
BIFOLD-BigEarthNetv2-0/BENv2-resnet101-s2-v0.1.1	BIFOLD-BigEarthNetv2-0	"2024-06-19T14:39:07Z"	0	transformers	[ "transformers", "safetensors", "model_hub_mixin", "pytorch_model_hub_mixin", "endpoints_compatible", "region:us" ]	null	"2024-06-16T20:40:36Z"	--- tags: - model_hub_mixin - pytorch_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]
SZ0/sha	SZ0	"2024-06-17T21:47:39Z"	0	null	[ "region:us" ]	null	"2024-06-16T20:51:37Z"	Entry not found
BIFOLD-BigEarthNetv2-0/BENv2-mixer_b16_224-s1-v0.1.1	BIFOLD-BigEarthNetv2-0	"2024-06-19T15:17:07Z"	0	transformers	[ "transformers", "safetensors", "model_hub_mixin", "pytorch_model_hub_mixin", "endpoints_compatible", "region:us" ]	null	"2024-06-16T20:51:53Z"	--- tags: - model_hub_mixin - pytorch_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]
arloo/Iggy_Azalea	arloo	"2024-06-16T20:59:22Z"	0	null	[ "region:us" ]	null	"2024-06-16T20:56:37Z"	Entry not found
Augusto777/swinv2-tiny-patch4-window8-256-ve-UH	Augusto777	"2024-06-16T21:07:34Z"	0	transformers	[ "transformers", "tensorboard", "safetensors", "swinv2", "image-classification", "generated_from_trainer", "base_model:microsoft/swinv2-tiny-patch4-window8-256", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	"2024-06-16T20:59:33Z"	--- license: apache-2.0 base_model: microsoft/swinv2-tiny-patch4-window8-256 tags: - generated_from_trainer metrics: - accuracy model-index: - name: swinv2-tiny-patch4-window8-256-ve-UH 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. --> # swinv2-tiny-patch4-window8-256-ve-UH This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.0154 - Accuracy: 0.7115 ## 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: 4e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 80 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| No log \| 1.0 \| 2 \| 1.6092 \| 0.4038 \| \| No log \| 2.0 \| 4 \| 1.6075 \| 0.4231 \| \| No log \| 3.0 \| 6 \| 1.6037 \| 0.4038 \| \| No log \| 4.0 \| 8 \| 1.5960 \| 0.4038 \| \| 1.6041 \| 5.0 \| 10 \| 1.5820 \| 0.4038 \| \| 1.6041 \| 6.0 \| 12 \| 1.5578 \| 0.4038 \| \| 1.6041 \| 7.0 \| 14 \| 1.5218 \| 0.4038 \| \| 1.6041 \| 8.0 \| 16 \| 1.4849 \| 0.4038 \| \| 1.6041 \| 9.0 \| 18 \| 1.4459 \| 0.4038 \| \| 1.4962 \| 10.0 \| 20 \| 1.4109 \| 0.4038 \| \| 1.4962 \| 11.0 \| 22 \| 1.3941 \| 0.4038 \| \| 1.4962 \| 12.0 \| 24 \| 1.3865 \| 0.4038 \| \| 1.4962 \| 13.0 \| 26 \| 1.3754 \| 0.4038 \| \| 1.4962 \| 14.0 \| 28 \| 1.3655 \| 0.4038 \| \| 1.3392 \| 15.0 \| 30 \| 1.3794 \| 0.4038 \| \| 1.3392 \| 16.0 \| 32 \| 1.3800 \| 0.4038 \| \| 1.3392 \| 17.0 \| 34 \| 1.3404 \| 0.4038 \| \| 1.3392 \| 18.0 \| 36 \| 1.3337 \| 0.4038 \| \| 1.3392 \| 19.0 \| 38 \| 1.3602 \| 0.4038 \| \| 1.2738 \| 20.0 \| 40 \| 1.3384 \| 0.4038 \| \| 1.2738 \| 21.0 \| 42 \| 1.3248 \| 0.4038 \| \| 1.2738 \| 22.0 \| 44 \| 1.2693 \| 0.4038 \| \| 1.2738 \| 23.0 \| 46 \| 1.2395 \| 0.4038 \| \| 1.2738 \| 24.0 \| 48 \| 1.2427 \| 0.4038 \| \| 1.2283 \| 25.0 \| 50 \| 1.2885 \| 0.4038 \| \| 1.2283 \| 26.0 \| 52 \| 1.2916 \| 0.4038 \| \| 1.2283 \| 27.0 \| 54 \| 1.2353 \| 0.4038 \| \| 1.2283 \| 28.0 \| 56 \| 1.2032 \| 0.4038 \| \| 1.2283 \| 29.0 \| 58 \| 1.2100 \| 0.5577 \| \| 1.1804 \| 30.0 \| 60 \| 1.2110 \| 0.6154 \| \| 1.1804 \| 31.0 \| 62 \| 1.1710 \| 0.6346 \| \| 1.1804 \| 32.0 \| 64 \| 1.1323 \| 0.6154 \| \| 1.1804 \| 33.0 \| 66 \| 1.1083 \| 0.5962 \| \| 1.1804 \| 34.0 \| 68 \| 1.0935 \| 0.5962 \| \| 1.0925 \| 35.0 \| 70 \| 1.0853 \| 0.6346 \| \| 1.0925 \| 36.0 \| 72 \| 1.0622 \| 0.6731 \| \| 1.0925 \| 37.0 \| 74 \| 1.0154 \| 0.7115 \| \| 1.0925 \| 38.0 \| 76 \| 0.9901 \| 0.7115 \| \| 1.0925 \| 39.0 \| 78 \| 0.9925 \| 0.6923 \| \| 0.9981 \| 40.0 \| 80 \| 0.9865 \| 0.6731 \| \| 0.9981 \| 41.0 \| 82 \| 0.9540 \| 0.6731 \| \| 0.9981 \| 42.0 \| 84 \| 0.9316 \| 0.7115 \| \| 0.9981 \| 43.0 \| 86 \| 0.9304 \| 0.7115 \| \| 0.9981 \| 44.0 \| 88 \| 0.9246 \| 0.6923 \| \| 0.9102 \| 45.0 \| 90 \| 0.8785 \| 0.7115 \| \| 0.9102 \| 46.0 \| 92 \| 0.8422 \| 0.7115 \| \| 0.9102 \| 47.0 \| 94 \| 0.8381 \| 0.7115 \| \| 0.9102 \| 48.0 \| 96 \| 0.8359 \| 0.7115 \| \| 0.9102 \| 49.0 \| 98 \| 0.8444 \| 0.7115 \| \| 0.8496 \| 50.0 \| 100 \| 0.8287 \| 0.6731 \| \| 0.8496 \| 51.0 \| 102 \| 0.7973 \| 0.6923 \| \| 0.8496 \| 52.0 \| 104 \| 0.7799 \| 0.6923 \| \| 0.8496 \| 53.0 \| 106 \| 0.7780 \| 0.6923 \| \| 0.8496 \| 54.0 \| 108 \| 0.7820 \| 0.7115 \| \| 0.7808 \| 55.0 \| 110 \| 0.7896 \| 0.7115 \| \| 0.7808 \| 56.0 \| 112 \| 0.7737 \| 0.6923 \| \| 0.7808 \| 57.0 \| 114 \| 0.7631 \| 0.6731 \| \| 0.7808 \| 58.0 \| 116 \| 0.7635 \| 0.6538 \| \| 0.7808 \| 59.0 \| 118 \| 0.7779 \| 0.6538 \| \| 0.757 \| 60.0 \| 120 \| 0.7990 \| 0.6731 \| \| 0.757 \| 61.0 \| 122 \| 0.8222 \| 0.6538 \| \| 0.757 \| 62.0 \| 124 \| 0.8204 \| 0.6538 \| \| 0.757 \| 63.0 \| 126 \| 0.7964 \| 0.6731 \| \| 0.757 \| 64.0 \| 128 \| 0.7818 \| 0.6538 \| \| 0.6919 \| 65.0 \| 130 \| 0.7796 \| 0.6346 \| \| 0.6919 \| 66.0 \| 132 \| 0.7831 \| 0.6346 \| \| 0.6919 \| 67.0 \| 134 \| 0.7867 \| 0.6346 \| \| 0.6919 \| 68.0 \| 136 \| 0.7856 \| 0.6346 \| \| 0.6919 \| 69.0 \| 138 \| 0.7793 \| 0.6538 \| \| 0.6722 \| 70.0 \| 140 \| 0.7736 \| 0.6538 \| \| 0.6722 \| 71.0 \| 142 \| 0.7682 \| 0.6538 \| \| 0.6722 \| 72.0 \| 144 \| 0.7681 \| 0.6538 \| \| 0.6722 \| 73.0 \| 146 \| 0.7672 \| 0.6538 \| \| 0.6722 \| 74.0 \| 148 \| 0.7655 \| 0.6538 \| \| 0.6642 \| 75.0 \| 150 \| 0.7645 \| 0.6538 \| \| 0.6642 \| 76.0 \| 152 \| 0.7658 \| 0.6538 \| \| 0.6642 \| 77.0 \| 154 \| 0.7677 \| 0.6538 \| \| 0.6642 \| 78.0 \| 156 \| 0.7683 \| 0.6538 \| \| 0.6642 \| 79.0 \| 158 \| 0.7684 \| 0.6538 \| \| 0.6491 \| 80.0 \| 160 \| 0.7686 \| 0.6538 \| ### Framework versions - Transformers 4.36.2 - Pytorch 2.1.2+cu118 - Datasets 2.16.1 - Tokenizers 0.15.0
tgama/wem_sentiment_model_v2	tgama	"2024-06-20T18:03:20Z"	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	"2024-06-16T21:00:04Z"	--- 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: tgama - 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)
Auart/klm	Auart	"2024-06-23T10:21:47Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T21:00:05Z"	--- license: openrail ---
pascal-maker/paligemma_vqav2	pascal-maker	"2024-06-16T21:01:39Z"	0	null	[ "region:us" ]	null	"2024-06-16T21:01:39Z"	Entry not found
BIFOLD-BigEarthNetv2-0/BENv2-resnet101-all-v0.1.1	BIFOLD-BigEarthNetv2-0	"2024-06-19T14:50:42Z"	0	transformers	[ "transformers", "safetensors", "model_hub_mixin", "pytorch_model_hub_mixin", "endpoints_compatible", "region:us" ]	null	"2024-06-16T21:03:12Z"	--- tags: - model_hub_mixin - pytorch_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]
BIFOLD-BigEarthNetv2-0/BENv2-mixer_b16_224-all-v0.1.1	BIFOLD-BigEarthNetv2-0	"2024-06-19T15:10:19Z"	0	transformers	[ "transformers", "safetensors", "model_hub_mixin", "pytorch_model_hub_mixin", "endpoints_compatible", "region:us" ]	null	"2024-06-16T21:03:54Z"	--- tags: - model_hub_mixin - pytorch_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]
Avalonus/Griffith	Avalonus	"2024-06-16T21:42:58Z"	0	null	[ "region:us" ]	null	"2024-06-16T21:04:52Z"	Entry not found
Edgar404/donut-shivi-cheques_pruning_0.5	Edgar404	"2024-06-19T22:57:12Z"	0	transformers	[ "transformers", "safetensors", "vision-encoder-decoder", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	"2024-06-16T21:07:44Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Augusto777/vit-base-patch16-224-dmae-TS	Augusto777	"2024-06-16T21:42:04Z"	0	transformers	[ "transformers", "tensorboard", "safetensors", "vit", "image-classification", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	"2024-06-16T21:07:55Z"	Entry not found
liminerity/duck-unsloth.F16.gguf	liminerity	"2024-06-16T21:08:31Z"	0	transformers	[ "transformers", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:liminerity/m7-64-bitnet-alpaca-1", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	"2024-06-16T21:08:30Z"	--- language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl base_model: liminerity/m7-64-bitnet-alpaca-1 --- # Uploaded model - Developed by: liminerity - License: apache-2.0 - Finetuned from model : liminerity/m7-64-bitnet-alpaca-1 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)
Augusto777/swinv2-tiny-patch4-window8-256-ve-UH2	Augusto777	"2024-06-16T21:16:56Z"	0	transformers	[ "transformers", "tensorboard", "safetensors", "swinv2", "image-classification", "generated_from_trainer", "base_model:microsoft/swinv2-tiny-patch4-window8-256", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	"2024-06-16T21:08:49Z"	--- license: apache-2.0 base_model: microsoft/swinv2-tiny-patch4-window8-256 tags: - generated_from_trainer metrics: - accuracy model-index: - name: swinv2-tiny-patch4-window8-256-ve-UH2 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. --> # swinv2-tiny-patch4-window8-256-ve-UH2 This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.7448 - Accuracy: 0.7308 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 80 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| No log \| 1.0 \| 2 \| 1.6091 \| 0.4038 \| \| No log \| 2.0 \| 4 \| 1.6070 \| 0.4231 \| \| No log \| 3.0 \| 6 \| 1.6017 \| 0.4038 \| \| No log \| 4.0 \| 8 \| 1.5911 \| 0.4038 \| \| 1.6022 \| 5.0 \| 10 \| 1.5707 \| 0.4038 \| \| 1.6022 \| 6.0 \| 12 \| 1.5355 \| 0.4038 \| \| 1.6022 \| 7.0 \| 14 \| 1.4951 \| 0.4038 \| \| 1.6022 \| 8.0 \| 16 \| 1.4528 \| 0.4038 \| \| 1.6022 \| 9.0 \| 18 \| 1.4096 \| 0.4038 \| \| 1.4645 \| 10.0 \| 20 \| 1.3820 \| 0.4038 \| \| 1.4645 \| 11.0 \| 22 \| 1.4055 \| 0.4038 \| \| 1.4645 \| 12.0 \| 24 \| 1.3765 \| 0.4038 \| \| 1.4645 \| 13.0 \| 26 \| 1.3820 \| 0.4038 \| \| 1.4645 \| 14.0 \| 28 \| 1.3712 \| 0.4038 \| \| 1.3172 \| 15.0 \| 30 \| 1.3546 \| 0.4038 \| \| 1.3172 \| 16.0 \| 32 \| 1.3637 \| 0.4038 \| \| 1.3172 \| 17.0 \| 34 \| 1.3646 \| 0.4038 \| \| 1.3172 \| 18.0 \| 36 \| 1.3271 \| 0.4038 \| \| 1.3172 \| 19.0 \| 38 \| 1.3084 \| 0.4038 \| \| 1.2549 \| 20.0 \| 40 \| 1.3402 \| 0.4038 \| \| 1.2549 \| 21.0 \| 42 \| 1.3550 \| 0.4038 \| \| 1.2549 \| 22.0 \| 44 \| 1.2677 \| 0.4038 \| \| 1.2549 \| 23.0 \| 46 \| 1.2093 \| 0.4038 \| \| 1.2549 \| 24.0 \| 48 \| 1.2040 \| 0.4231 \| \| 1.2092 \| 25.0 \| 50 \| 1.2963 \| 0.4231 \| \| 1.2092 \| 26.0 \| 52 \| 1.2917 \| 0.4808 \| \| 1.2092 \| 27.0 \| 54 \| 1.1798 \| 0.5769 \| \| 1.2092 \| 28.0 \| 56 \| 1.1047 \| 0.6346 \| \| 1.2092 \| 29.0 \| 58 \| 1.0923 \| 0.6731 \| \| 1.1321 \| 30.0 \| 60 \| 1.1066 \| 0.6538 \| \| 1.1321 \| 31.0 \| 62 \| 1.0874 \| 0.6538 \| \| 1.1321 \| 32.0 \| 64 \| 1.0548 \| 0.6731 \| \| 1.1321 \| 33.0 \| 66 \| 1.0012 \| 0.6538 \| \| 1.1321 \| 34.0 \| 68 \| 0.9641 \| 0.6923 \| \| 1.0022 \| 35.0 \| 70 \| 0.9796 \| 0.6538 \| \| 1.0022 \| 36.0 \| 72 \| 0.9631 \| 0.6538 \| \| 1.0022 \| 37.0 \| 74 \| 0.9040 \| 0.6731 \| \| 1.0022 \| 38.0 \| 76 \| 0.8731 \| 0.6923 \| \| 1.0022 \| 39.0 \| 78 \| 0.8960 \| 0.6731 \| \| 0.8941 \| 40.0 \| 80 \| 0.9133 \| 0.6538 \| \| 0.8941 \| 41.0 \| 82 \| 0.8507 \| 0.6923 \| \| 0.8941 \| 42.0 \| 84 \| 0.8064 \| 0.7115 \| \| 0.8941 \| 43.0 \| 86 \| 0.8075 \| 0.7115 \| \| 0.8941 \| 44.0 \| 88 \| 0.8486 \| 0.6923 \| \| 0.7866 \| 45.0 \| 90 \| 0.8075 \| 0.6923 \| \| 0.7866 \| 46.0 \| 92 \| 0.7496 \| 0.6731 \| \| 0.7866 \| 47.0 \| 94 \| 0.7431 \| 0.6731 \| \| 0.7866 \| 48.0 \| 96 \| 0.7442 \| 0.6731 \| \| 0.7866 \| 49.0 \| 98 \| 0.7735 \| 0.6923 \| \| 0.7281 \| 50.0 \| 100 \| 0.7751 \| 0.6923 \| \| 0.7281 \| 51.0 \| 102 \| 0.7370 \| 0.6923 \| \| 0.7281 \| 52.0 \| 104 \| 0.7230 \| 0.6923 \| \| 0.7281 \| 53.0 \| 106 \| 0.7314 \| 0.6923 \| \| 0.7281 \| 54.0 \| 108 \| 0.7498 \| 0.6731 \| \| 0.6725 \| 55.0 \| 110 \| 0.7557 \| 0.6731 \| \| 0.6725 \| 56.0 \| 112 \| 0.7314 \| 0.7115 \| \| 0.6725 \| 57.0 \| 114 \| 0.7334 \| 0.7115 \| \| 0.6725 \| 58.0 \| 116 \| 0.7375 \| 0.7115 \| \| 0.6725 \| 59.0 \| 118 \| 0.7434 \| 0.6923 \| \| 0.6526 \| 60.0 \| 120 \| 0.7548 \| 0.6731 \| \| 0.6526 \| 61.0 \| 122 \| 0.7813 \| 0.7115 \| \| 0.6526 \| 62.0 \| 124 \| 0.7722 \| 0.6923 \| \| 0.6526 \| 63.0 \| 126 \| 0.7469 \| 0.6923 \| \| 0.6526 \| 64.0 \| 128 \| 0.7402 \| 0.6731 \| \| 0.5915 \| 65.0 \| 130 \| 0.7448 \| 0.7308 \| \| 0.5915 \| 66.0 \| 132 \| 0.7467 \| 0.6923 \| \| 0.5915 \| 67.0 \| 134 \| 0.7496 \| 0.6731 \| \| 0.5915 \| 68.0 \| 136 \| 0.7518 \| 0.7308 \| \| 0.5915 \| 69.0 \| 138 \| 0.7453 \| 0.7115 \| \| 0.578 \| 70.0 \| 140 \| 0.7385 \| 0.6923 \| \| 0.578 \| 71.0 \| 142 \| 0.7411 \| 0.6731 \| \| 0.578 \| 72.0 \| 144 \| 0.7442 \| 0.6731 \| \| 0.578 \| 73.0 \| 146 \| 0.7440 \| 0.6731 \| \| 0.578 \| 74.0 \| 148 \| 0.7428 \| 0.6923 \| \| 0.5826 \| 75.0 \| 150 \| 0.7414 \| 0.6923 \| \| 0.5826 \| 76.0 \| 152 \| 0.7416 \| 0.6923 \| \| 0.5826 \| 77.0 \| 154 \| 0.7414 \| 0.6923 \| \| 0.5826 \| 78.0 \| 156 \| 0.7413 \| 0.6731 \| \| 0.5826 \| 79.0 \| 158 \| 0.7413 \| 0.6731 \| \| 0.5586 \| 80.0 \| 160 \| 0.7415 \| 0.6923 \| ### Framework versions - Transformers 4.36.2 - Pytorch 2.1.2+cu118 - Datasets 2.16.1 - Tokenizers 0.15.0
RichardErkhov/mlabonne_-_Daredevil-8B-abliterated-gguf	RichardErkhov	"2024-06-16T21:09:38Z"	0	null	[ "region:us" ]	null	"2024-06-16T21:09:38Z"	Entry not found
Dani3lRg/sentiment-analysis-distilbert	Dani3lRg	"2024-06-16T21:09:44Z"	0	null	[ "region:us" ]	null	"2024-06-16T21:09:44Z"	Entry not found
RichardErkhov/Toten5_-_Marcoroni-neural-chat-7B-v2-gguf	RichardErkhov	"2024-06-16T21:10:08Z"	0	null	[ "region:us" ]	null	"2024-06-16T21:10:08Z"	Entry not found
AriaRahmati1/222shesmat2	AriaRahmati1	"2024-06-16T23:00:59Z"	0	null	[ "license:openrail", "region:us" ]	null	"2024-06-16T21:12:19Z"	--- license: openrail ---

Tinuva/MidkemiaAnimeTV

Tinuva

"2024-06-16T17:54:42Z"

0

null

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

null

"2024-06-16T17:44:04Z"

--- license: creativeml-openrail-m ---

fruk19/whisper-thai-north

fruk19

"2024-06-16T17:48:09Z"

0

null

[ "region:us" ]

null

"2024-06-16T17:48:09Z"

Entry not found

clxudiajazmin/ClaudiaSoria_TFM_V4

clxudiajazmin

"2024-06-17T12:00:17Z"

0

transformers

[ "transformers", "safetensors", "t5", "text2text-generation", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]

text2text-generation

"2024-06-16T17:49:00Z"

Entry not found

lhbit20010120/without_vg_refcoco_model

lhbit20010120

"2024-06-16T17:50:43Z"

0

null

[ "region:us" ]

null

"2024-06-16T17:50:43Z"

Entry not found

fruk19/thainorthmodel

fruk19

"2024-06-16T18:13:42Z"

0

transformers

[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

"2024-06-16T18:00:51Z"

Entry not found

menglc/deepstack-l-vicuna-7b

menglc

"2024-06-17T03:18:58Z"

0

transformers

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

text-generation

"2024-06-16T18:03:55Z"

--- license: apache-2.0 ---

samannar/ddduva

samannar

"2024-06-16T18:03:57Z"

0

null

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

null

"2024-06-16T18:03:57Z"

--- license: openrail ---

Jareen/tesing

Jareen

"2024-06-16T18:07:38Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:07:38Z"

Entry not found

SeoulStreamingStation/KLM4

SeoulStreamingStation

"2024-06-16T19:14:36Z"

0

5

null

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

null

"2024-06-16T18:12:13Z"

--- license: other license_name: sss license_link: LICENSE ---

moschouChry/chronos-t5-finetuned_small_1-Patient0-fine-tuned_20240616_205512

moschouChry

"2024-06-16T18:14:56Z"

0

transformers

[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]

text2text-generation

"2024-06-16T18:14:39Z"

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

SilvioLima/absa_treinamento_2

SilvioLima

"2024-06-16T19:05:14Z"

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]

text-generation

"2024-06-16T18:15:40Z"

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

north/llama2_DensityExperiment_filtered80-70k-exporttest

north

"2024-06-16T18:26:02Z"

0

transformers

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

text-generation

"2024-06-16T18:17:01Z"

Entry not found

Emmanuel132/Mack_dm690s

Emmanuel132

"2024-06-16T18:19:35Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:19:34Z"

Entry not found

EugeneShally/whisper-small-nl

EugeneShally

"2024-06-17T05:27:31Z"

0

transformers

[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

"2024-06-16T18:24:57Z"

Entry not found

Mohammed-majeed/llama-3-8b-bnb-4bit-Unsloth-chunk-7-0.5-2

Mohammed-majeed

"2024-06-16T18:26:57Z"

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

"2024-06-16T18:25:56Z"

--- 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:** Mohammed-majeed - **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)

bfrenan/Llama3-log-to-ttp-lora-adapters_2

bfrenan

"2024-06-16T18:29:46Z"

0

transformers

[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:unsloth/llama-3-8b-Instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

"2024-06-16T18:29:38Z"

--- language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl base_model: unsloth/llama-3-8b-Instruct-bnb-4bit --- # Uploaded model - **Developed by:** bfrenan - **License:** apache-2.0 - **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

bfrenan/Llama3-log-to-ttp-tokenizer_2

bfrenan

"2024-06-16T18:29:48Z"

0

transformers

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

null

"2024-06-16T18:29:47Z"

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

Fawazzx/alzheimer_classification_using_resnet50_finetuned

Fawazzx

"2024-06-16T21:37:29Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:30:25Z"

# Fine-Tuning ResNet50 for Alzheimer's MRI Classification This repository contains a Jupyter Notebook for fine-tuning a ResNet50 model to classify Alzheimer's disease stages from MRI images. The notebook uses PyTorch and the dataset is loaded from the Hugging Face Datasets library. ## Table of Contents - [Introduction](#introduction) - [Dataset](#dataset) - [Model Architecture](#model-architecture) - [Setup](#setup) - [Training](#training) - [Evaluation](#evaluation) - [Usage](#usage) - [Results](#results) - [Contributing](#contributing) - [License](#license) ## Introduction This notebook fine-tunes a pre-trained ResNet50 model to classify MRI images into one of four stages of Alzheimer's disease: - Mild Demented - Moderate Demented - Non-Demented - Very Mild Demented ## Dataset The dataset used is [Falah/Alzheimer_MRI](https://huggingface.co/datasets/Falah/Alzheimer_MRI) from the Hugging Face Datasets library. It consists of MRI images categorized into the four stages of Alzheimer's disease. ## Model Architecture The model architecture is based on ResNet50. The final fully connected layer is modified to output predictions for 4 classes. ## Setup To run the notebook locally, follow these steps: 1. Clone the repository: ```bash git clone https://github.com/your_username/alzheimer_mri_classification.git cd alzheimer_mri_classification ``` 2. Install the required dependencies: ```bash pip install -r requirements.txt ``` 3. Open the notebook: ```bash jupyter notebook fine-tuning.ipynb ``` ## Training The notebook includes sections for: - Loading and preprocessing the dataset - Defining the model architecture - Setting up the training loop with a learning rate scheduler and optimizer - Training the model for a specified number of epochs - Saving the trained model weights ## Evaluation The notebook includes a section for evaluating the trained model on the validation set. It calculates and prints the validation loss and accuracy. ## Usage Once trained, the model can be saved and used for inference on new MRI images. The trained model weights are saved as alzheimer_model_resnet50.pth. ## Load the model architecture and weights ```python model = models.resnet50(weights=None) model.fc = nn.Linear(model.fc.in_features, 4) model.load_state_dict(torch.load("alzheimer_model_resnet50.pth", map_location=torch.device('cpu'))) model.eval() ``` ## Results The model achieved an accuracy of 95.9375% on the validation set. ## Contributing Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request.

seashorers/GRAGAS

seashorers

"2024-06-17T00:52:46Z"

0

null

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

null

"2024-06-16T18:30:39Z"

--- license: openrail ---

hngan/cocowholebody

hngan

"2024-06-16T18:40:21Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:31:24Z"

Entry not found

SukritSNegi/Llama-2-7b-chat-new-finetune

SukritSNegi

"2024-06-22T10:47:39Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:38:43Z"

Entry not found

dtruong46me/flant5-large-lora

dtruong46me

"2024-06-16T18:41:25Z"

0

peft

[ "peft", "safetensors", "generated_from_trainer", "base_model:google/flan-t5-large", "license:apache-2.0", "region:us" ]

null

"2024-06-16T18:41:15Z"

--- license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: google/flan-t5-large metrics: - rouge model-index: - name: flant5-large-lora results: [] ---  # flant5-large-lora This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6119 - Rouge1: 8.9675 - Rouge2: 0.6714 - Rougel: 8.0407 - Rougelsum: 8.3753 - Gen Len: 18.37 ## 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: 6 - eval_batch_size: 6 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | 1.8402 | 1.0 | 1538 | 0.7486 | 8.8441 | 0.6859 | 7.9731 | 8.3103 | 19.502 | | 0.8152 | 2.0 | 3076 | 0.6119 | 8.9675 | 0.6714 | 8.0407 | 8.3753 | 18.37 | ### Framework versions - PEFT 0.11.1 - Transformers 4.36.1 - Pytorch 2.1.2 - Datasets 2.20.0 - Tokenizers 0.15.2

moschouChry/chronos-t5-finetuned_small_1-Patient0-fine-tuned_20240616_205441

moschouChry

"2024-06-16T18:42:24Z"

0

transformers

[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]

text2text-generation

"2024-06-16T18:42:10Z"

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

PLS442/Yoko

PLS442

"2024-06-16T18:43:49Z"

0

null

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

null

"2024-06-16T18:43:02Z"

--- license: openrail ---

coco233/run

coco233

"2024-06-16T18:44:35Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:43:28Z"

Entry not found

abyesses/results

abyesses

"2024-06-16T18:43:56Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:43:56Z"

Entry not found

gamallo/translator-gl-zh

gamallo

"2024-06-16T22:16:38Z"

0

null

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

null

"2024-06-16T18:44:02Z"

--- license: mit --- **How to translate with this model** + Install [Python 3.9](https://www.python.org/downloads/release/python-390/) + ctranslate 2 + subword-nmt ```bash pip install ctranslate2~=3.20.0 ``` ```bash pip install subword-nmt ``` + tokenization with BPE: ```bash subword-nmt apply-bpe -c gl-detok10k.code < input_file.txt > input_file_bpe.txt ``` + Translating an input_text using ct2_detok-gl-zh: ```bash python3 trans_ct2.py ct2_detok-gl-zh input_file_bpe.txt >output_file_bpe.txt ``` + DeBPEar output txt: ```bash cat out_test_bpe.txt | sed "s/@@ //g" > output_file.txt ``` **Acknowledgments** Thanks to Tang Waying, Zheng Jie and Wang Tianjiao for helping prepare the parallel corpora.

puipuipui/zee

puipuipui

"2024-06-16T19:12:53Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:44:14Z"

Entry not found

lucao123/h-an-m-model

lucao123

"2024-06-16T18:46:44Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:46:43Z"

Entry not found

Paco4365483/Finetune10

Paco4365483

"2024-06-16T19:02:31Z"

0

transformers

[ "transformers", "safetensors", "llava_llama", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-generation

"2024-06-16T18:50:52Z"

Entry not found

strwbrylily/Im-Nayeon-by-strwbrylily

strwbrylily

"2024-06-16T18:55:29Z"

0

null

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

null

"2024-06-16T18:54:50Z"

--- license: openrail ---

numen-tech/Llama-3-WhiteRabbitNeo-8B-v2.0-w4a16g128asym

numen-tech

"2024-06-16T19:00:17Z"

0

null

[ "arxiv:2308.13137", "license:llama3", "region:us" ]

null

"2024-06-16T18:55:34Z"

--- license: llama3 --- 4-bit [OmniQuant](https://arxiv.org/abs/2308.13137) quantized version of [Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0).

codingninja/testing

codingninja

"2024-06-16T18:55:43Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:55:43Z"

Entry not found

numen-tech/Llama-3-WhiteRabbitNeo-8B-v2.0-w3a16g40sym

numen-tech

"2024-06-16T19:00:26Z"

0

null

[ "arxiv:2308.13137", "license:llama3", "region:us" ]

null

"2024-06-16T18:56:01Z"

--- license: llama3 --- 3-bit [OmniQuant](https://arxiv.org/abs/2308.13137) quantized version of [Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0).

kaitr/opt-6.7b-lora

kaitr

"2024-06-16T18:59:00Z"

0

null

[ "region:us" ]

null

"2024-06-16T18:59:00Z"

Entry not found

AndreMitri/BERT_cls_polaridade

AndreMitri

"2024-06-16T19:05:22Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:04:20Z"

Entry not found

Danyt24/finetuning-sentiment-model-4000-samples

Danyt24

"2024-06-16T19:06:29Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:06:29Z"

Entry not found

HotDrify/thelemyAI

HotDrify

"2024-06-16T19:06:31Z"

0

null

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

null

"2024-06-16T19:06:31Z"

--- license: mit ---

silent666/Qwen-Qwen1.5-7B-1718564795

silent666

"2024-06-16T19:06:38Z"

0

peft

[ "peft", "safetensors", "arxiv:1910.09700", "base_model:Qwen/Qwen1.5-7B", "region:us" ]

null

"2024-06-16T19:06:35Z"

--- base_model: Qwen/Qwen1.5-7B library_name: peft --- # Model Card for Model ID  ## Model Details ### Model Description  - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.11.1

iasjkk/MV_EC

iasjkk

"2024-06-24T09:49:07Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:07:21Z"

Entry not found

levipereira/yolov8n-trt

levipereira

"2024-06-16T19:08:44Z"

0

null

[ "license:agpl-3.0", "region:us" ]

null

"2024-06-16T19:08:43Z"

--- license: agpl-3.0 ---

Nibo4k/CantoraCreditos

Nibo4k

"2024-06-16T21:24:51Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:11:43Z"

Entry not found

Testvsls0224/test1model

Testvsls0224

"2024-06-17T01:57:50Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:11:58Z"

Entry not found

Damir4/izamodel

Damir4

"2024-06-16T19:12:05Z"

0

null

[ "license:gpl-3.0", "region:us" ]

null

"2024-06-16T19:12:05Z"

--- license: gpl-3.0 ---

vsls0224/testModel

vsls0224

"2024-06-16T19:13:10Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:13:10Z"

Entry not found

ahmedesmail16/0.50-800Train-100Test-beit-base

ahmedesmail16

"2024-06-17T00:18:58Z"

0

transformers

[ "transformers", "tensorboard", "safetensors", "beit", "image-classification", "generated_from_trainer", "base_model:microsoft/beit-base-patch16-224-pt22k-ft22k", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

"2024-06-16T19:16:41Z"

--- license: apache-2.0 base_model: microsoft/beit-base-patch16-224-pt22k-ft22k tags: - generated_from_trainer metrics: - accuracy model-index: - name: 0.50-800Train-100Test-beit-base results: [] ---  # 0.50-800Train-100Test-beit-base This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.7501 - Accuracy: 0.8192 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 512 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.7627 | 0.9536 | 18 | 0.6991 | 0.7860 | | 0.3414 | 1.9603 | 37 | 0.5881 | 0.8070 | | 0.1402 | 2.9669 | 56 | 0.5879 | 0.8114 | | 0.0663 | 3.9735 | 75 | 0.6249 | 0.8175 | | 0.0377 | 4.9801 | 94 | 0.6539 | 0.8210 | | 0.0314 | 5.9868 | 113 | 0.7074 | 0.8175 | | 0.0189 | 6.9934 | 132 | 0.7596 | 0.8210 | | 0.0147 | 8.0 | 151 | 0.7211 | 0.8253 | | 0.0157 | 8.9536 | 169 | 0.7412 | 0.8166 | | 0.0095 | 9.5364 | 180 | 0.7501 | 0.8192 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.1.2 - Datasets 2.19.2 - Tokenizers 0.19.1

Rrrr3/Hhk

Rrrr3

"2024-06-16T19:18:07Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:18:07Z"

Entry not found

andreluiz1/teste

andreluiz1

"2024-06-16T19:21:34Z"

0

null

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

null

"2024-06-16T19:21:34Z"

--- license: openrail ---

mjfan1999/LukeCombs2024

mjfan1999

"2024-06-16T19:32:06Z"

0

null

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

null

"2024-06-16T19:22:29Z"

--- license: unknown ---

dostoewslybtw/portal_of_i

dostoewslybtw

"2024-06-16T19:24:01Z"

0

null

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

null

"2024-06-16T19:24:01Z"

--- license: apache-2.0 ---

moschouChry/chronos-t5-finetuned_small_1-Patient0-fine-tuned_20240616_205414

moschouChry

"2024-06-16T19:25:11Z"

0

transformers

[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]

text2text-generation

"2024-06-16T19:24:57Z"

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

codingninja/openchat-7b-galbaat

codingninja

"2024-06-21T13:22:07Z"

0

null

[ "tensorboard", "safetensors", "region:us" ]

null

"2024-06-16T19:25:09Z"

Entry not found

royvdkoelen/DayZ

royvdkoelen

"2024-06-16T19:26:24Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:26:24Z"

Entry not found

matthewleechen/yolov8s_ukpatents_singleclass

matthewleechen

"2024-06-16T19:27:14Z"

0

null

[ "tensorboard", "region:us" ]

null

"2024-06-16T19:26:30Z"

Entry not found

aerainyourarea/S1Seoyeon

aerainyourarea

"2024-06-16T19:34:03Z"

0

null

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

null

"2024-06-16T19:26:40Z"

--- license: openrail ---

Marco127/llamantino_hodi_requalification

Marco127

"2024-06-16T21:45:13Z"

0

transformers

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

null

"2024-06-16T19:28:21Z"

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

JhuTheBunny999/Frey

JhuTheBunny999

"2024-06-20T09:39:04Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:31:48Z"

Entry not found

strwbrylily/Kim-Jiwoo-RUNext-by-strwbrylily

strwbrylily

"2024-06-16T19:34:11Z"

0

null

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

null

"2024-06-16T19:31:51Z"

--- license: openrail ---

TheMindExpansionNetwork/m1nd3xpand3r-1024x1024-sd3-lora

TheMindExpansionNetwork

"2024-06-16T19:36:26Z"

0

null

[ "region:us" ]

null

"2024-06-16T19:36:26Z"

Entry not found

Mortello/q-FrozenLake-v1

Mortello

"2024-06-16T19:36:51Z"

0

null

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

reinforcement-learning

"2024-06-16T19:36:48Z"

--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **FrozenLake-v1** This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** . ## Usage ```python model = load_from_hub(repo_id="Mortello/q-FrozenLake-v1", 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"]) ```

T-ZERO/first_prototype

T-ZERO

"2024-06-16T19:44:23Z"

0

flair

[ "flair", "legal", "text-generation", "fa", "dataset:OpenGVLab/ShareGPT-4o", "license:llama3", "region:us" ]

text-generation

"2024-06-16T19:38:26Z"

--- license: llama3 datasets: - OpenGVLab/ShareGPT-4o language: - fa metrics: - character library_name: flair pipeline_tag: text-generation tags: - legal ---

IlyaGusev/saiga_llama3_70b_sft_m1_d5_abliterated_kto_m1_d2_lora

IlyaGusev

"2024-06-16T19:42:25Z"

0

null

[ "safetensors", "region:us" ]

null

"2024-06-16T19:39:29Z"

Entry not found

Mortello/q-Taxi-v3

Mortello

"2024-06-16T19:43:32Z"

0

null

[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]

reinforcement-learning

"2024-06-16T19:43:31Z"

--- 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: 7.54 +/- 2.74 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="Mortello/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"]) ```

kawagoshi-llm-team/test_40B

kawagoshi-llm-team

"2024-06-16T19:58:12Z"

0

transformers

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

text-generation

"2024-06-16T19:45:39Z"

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

menglc/deepstack-l-hd-vicuna-7b

menglc

"2024-06-17T03:08:34Z"

0

transformers

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

text-generation

"2024-06-16T19:49:03Z"

--- license: apache-2.0 ---

stojchet/python-sft-r64-a16-d0.05-e3

stojchet

"2024-06-16T19:54:05Z"

0

peft

[ "peft", "safetensors", "trl", "sft", "generated_from_trainer", "dataset:generator", "base_model:deepseek-ai/deepseek-coder-1.3b-base", "license:other", "region:us" ]

null

"2024-06-16T19:53:59Z"

--- base_model: deepseek-ai/deepseek-coder-1.3b-base datasets: - generator library_name: peft license: other tags: - trl - sft - generated_from_trainer model-index: - name: python-sft-r64-a16-d0.05-e3 results: [] ---  [<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/stojchets/huggingface/runs/rmvtpvu9) # python-sft-r64-a16-d0.05-e3 This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on the generator 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: 1.41e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results ### Framework versions - PEFT 0.10.0 - Transformers 4.42.0.dev0 - Pytorch 2.2.2+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1

BIFOLD-BigEarthNetv2-0/BENv2-resnet50-s1-v0.1.1

BIFOLD-BigEarthNetv2-0

"2024-06-19T14:09:01Z"

0

transformers

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

null

"2024-06-16T19:57:51Z"

--- tags: - model_hub_mixin - pytorch_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]

pwl15/llava-v1.5-food101

pwl15

"2024-06-17T18:52:42Z"

0

null

[ "safetensors", "region:us" ]

null

"2024-06-16T19:59:04Z"

Entry not found

kohapahm/distilhubert-finetuned-gtzan

kohapahm

"2024-06-16T20:00:38Z"

0

null

[ "region:us" ]

null

"2024-06-16T20:00:38Z"

Entry not found

CLASS-MATE/llama2-train_test

CLASS-MATE

"2024-06-17T22:40:18Z"

0

transformers

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

null

"2024-06-16T20:03:31Z"

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

xpozryx/ponyRealisticTrainingColab

xpozryx

"2024-06-16T21:59:23Z"

0

null

[ "region:us" ]

null

"2024-06-16T20:07:59Z"

Entry not found

SkyWR/wgn

SkyWR

"2024-06-16T20:12:04Z"

0

null

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

null

"2024-06-16T20:09:32Z"

--- license: openrail ---

evitalyst/ChatMe

evitalyst

"2024-06-16T20:09:57Z"

0

null

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

null

"2024-06-16T20:09:57Z"

--- license: apache-2.0 ---

Yuseifer/Reinforce_model-cartpole

Yuseifer

"2024-06-16T20:10:22Z"

0

null

[ "CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class", "model-index", "region:us" ]

reinforcement-learning

"2024-06-16T20:10:13Z"

--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce_model-cartpole results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: - type: mean_reward value: 467.80 +/- 96.60 name: mean_reward verified: false --- # **Reinforce** Agent playing **CartPole-v1** This is a trained model of a **Reinforce** agent playing **CartPole-v1** . To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction

BIFOLD-BigEarthNetv2-0/BENv2-resnet101-s1-v0.1.1

BIFOLD-BigEarthNetv2-0

"2024-06-19T14:12:15Z"

0

transformers

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

null

"2024-06-16T20:10:41Z"

--- tags: - model_hub_mixin - pytorch_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]

sharad31/my_model

sharad31

"2024-06-16T20:12:02Z"

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

"2024-06-16T20:11:37Z"

--- 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:** sharad31 - **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)

shunsso/data

shunsso

"2024-06-16T20:19:13Z"

0

null

[ "region:us" ]

null

"2024-06-16T20:19:13Z"

Entry not found

Roo89/Ru

Roo89

"2024-06-16T20:19:36Z"

0

null

[ "region:us" ]

null

"2024-06-16T20:19:36Z"

Entry not found

GalaktischeGurke/whisper-large-v3_German_merge_ratio_ch_de_0.5

GalaktischeGurke

"2024-06-16T20:19:51Z"

0

null

[ "region:us" ]

null

"2024-06-16T20:19:51Z"

Entry not found

BIFOLD-BigEarthNetv2-0/BENv2-resnet50-s2-v0.1.1

BIFOLD-BigEarthNetv2-0

"2024-06-19T14:28:11Z"

0

transformers

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

null

"2024-06-16T20:22:36Z"

--- tags: - model_hub_mixin - pytorch_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]

sharad31/talktoyourself

sharad31

"2024-06-16T20:29:14Z"

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

"2024-06-16T20:29:04Z"

--- 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:** sharad31 - **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)

BIFOLD-BigEarthNetv2-0/BENv2-resnet101-s2-v0.1.1

BIFOLD-BigEarthNetv2-0

"2024-06-19T14:39:07Z"

0

transformers

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

null

"2024-06-16T20:40:36Z"

--- tags: - model_hub_mixin - pytorch_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]

SZ0/sha

SZ0

"2024-06-17T21:47:39Z"

0

null

[ "region:us" ]

null

"2024-06-16T20:51:37Z"

Entry not found

BIFOLD-BigEarthNetv2-0/BENv2-mixer_b16_224-s1-v0.1.1

BIFOLD-BigEarthNetv2-0

"2024-06-19T15:17:07Z"

0

transformers

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

null

"2024-06-16T20:51:53Z"

--- tags: - model_hub_mixin - pytorch_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]

arloo/Iggy_Azalea

arloo

"2024-06-16T20:59:22Z"

0

null

[ "region:us" ]

null

"2024-06-16T20:56:37Z"

Entry not found

Augusto777/swinv2-tiny-patch4-window8-256-ve-UH

Augusto777

"2024-06-16T21:07:34Z"

0

transformers

[ "transformers", "tensorboard", "safetensors", "swinv2", "image-classification", "generated_from_trainer", "base_model:microsoft/swinv2-tiny-patch4-window8-256", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

"2024-06-16T20:59:33Z"

--- license: apache-2.0 base_model: microsoft/swinv2-tiny-patch4-window8-256 tags: - generated_from_trainer metrics: - accuracy model-index: - name: swinv2-tiny-patch4-window8-256-ve-UH results: [] ---  # swinv2-tiny-patch4-window8-256-ve-UH This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.0154 - Accuracy: 0.7115 ## 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: 4e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 80 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 2 | 1.6092 | 0.4038 | | No log | 2.0 | 4 | 1.6075 | 0.4231 | | No log | 3.0 | 6 | 1.6037 | 0.4038 | | No log | 4.0 | 8 | 1.5960 | 0.4038 | | 1.6041 | 5.0 | 10 | 1.5820 | 0.4038 | | 1.6041 | 6.0 | 12 | 1.5578 | 0.4038 | | 1.6041 | 7.0 | 14 | 1.5218 | 0.4038 | | 1.6041 | 8.0 | 16 | 1.4849 | 0.4038 | | 1.6041 | 9.0 | 18 | 1.4459 | 0.4038 | | 1.4962 | 10.0 | 20 | 1.4109 | 0.4038 | | 1.4962 | 11.0 | 22 | 1.3941 | 0.4038 | | 1.4962 | 12.0 | 24 | 1.3865 | 0.4038 | | 1.4962 | 13.0 | 26 | 1.3754 | 0.4038 | | 1.4962 | 14.0 | 28 | 1.3655 | 0.4038 | | 1.3392 | 15.0 | 30 | 1.3794 | 0.4038 | | 1.3392 | 16.0 | 32 | 1.3800 | 0.4038 | | 1.3392 | 17.0 | 34 | 1.3404 | 0.4038 | | 1.3392 | 18.0 | 36 | 1.3337 | 0.4038 | | 1.3392 | 19.0 | 38 | 1.3602 | 0.4038 | | 1.2738 | 20.0 | 40 | 1.3384 | 0.4038 | | 1.2738 | 21.0 | 42 | 1.3248 | 0.4038 | | 1.2738 | 22.0 | 44 | 1.2693 | 0.4038 | | 1.2738 | 23.0 | 46 | 1.2395 | 0.4038 | | 1.2738 | 24.0 | 48 | 1.2427 | 0.4038 | | 1.2283 | 25.0 | 50 | 1.2885 | 0.4038 | | 1.2283 | 26.0 | 52 | 1.2916 | 0.4038 | | 1.2283 | 27.0 | 54 | 1.2353 | 0.4038 | | 1.2283 | 28.0 | 56 | 1.2032 | 0.4038 | | 1.2283 | 29.0 | 58 | 1.2100 | 0.5577 | | 1.1804 | 30.0 | 60 | 1.2110 | 0.6154 | | 1.1804 | 31.0 | 62 | 1.1710 | 0.6346 | | 1.1804 | 32.0 | 64 | 1.1323 | 0.6154 | | 1.1804 | 33.0 | 66 | 1.1083 | 0.5962 | | 1.1804 | 34.0 | 68 | 1.0935 | 0.5962 | | 1.0925 | 35.0 | 70 | 1.0853 | 0.6346 | | 1.0925 | 36.0 | 72 | 1.0622 | 0.6731 | | 1.0925 | 37.0 | 74 | 1.0154 | 0.7115 | | 1.0925 | 38.0 | 76 | 0.9901 | 0.7115 | | 1.0925 | 39.0 | 78 | 0.9925 | 0.6923 | | 0.9981 | 40.0 | 80 | 0.9865 | 0.6731 | | 0.9981 | 41.0 | 82 | 0.9540 | 0.6731 | | 0.9981 | 42.0 | 84 | 0.9316 | 0.7115 | | 0.9981 | 43.0 | 86 | 0.9304 | 0.7115 | | 0.9981 | 44.0 | 88 | 0.9246 | 0.6923 | | 0.9102 | 45.0 | 90 | 0.8785 | 0.7115 | | 0.9102 | 46.0 | 92 | 0.8422 | 0.7115 | | 0.9102 | 47.0 | 94 | 0.8381 | 0.7115 | | 0.9102 | 48.0 | 96 | 0.8359 | 0.7115 | | 0.9102 | 49.0 | 98 | 0.8444 | 0.7115 | | 0.8496 | 50.0 | 100 | 0.8287 | 0.6731 | | 0.8496 | 51.0 | 102 | 0.7973 | 0.6923 | | 0.8496 | 52.0 | 104 | 0.7799 | 0.6923 | | 0.8496 | 53.0 | 106 | 0.7780 | 0.6923 | | 0.8496 | 54.0 | 108 | 0.7820 | 0.7115 | | 0.7808 | 55.0 | 110 | 0.7896 | 0.7115 | | 0.7808 | 56.0 | 112 | 0.7737 | 0.6923 | | 0.7808 | 57.0 | 114 | 0.7631 | 0.6731 | | 0.7808 | 58.0 | 116 | 0.7635 | 0.6538 | | 0.7808 | 59.0 | 118 | 0.7779 | 0.6538 | | 0.757 | 60.0 | 120 | 0.7990 | 0.6731 | | 0.757 | 61.0 | 122 | 0.8222 | 0.6538 | | 0.757 | 62.0 | 124 | 0.8204 | 0.6538 | | 0.757 | 63.0 | 126 | 0.7964 | 0.6731 | | 0.757 | 64.0 | 128 | 0.7818 | 0.6538 | | 0.6919 | 65.0 | 130 | 0.7796 | 0.6346 | | 0.6919 | 66.0 | 132 | 0.7831 | 0.6346 | | 0.6919 | 67.0 | 134 | 0.7867 | 0.6346 | | 0.6919 | 68.0 | 136 | 0.7856 | 0.6346 | | 0.6919 | 69.0 | 138 | 0.7793 | 0.6538 | | 0.6722 | 70.0 | 140 | 0.7736 | 0.6538 | | 0.6722 | 71.0 | 142 | 0.7682 | 0.6538 | | 0.6722 | 72.0 | 144 | 0.7681 | 0.6538 | | 0.6722 | 73.0 | 146 | 0.7672 | 0.6538 | | 0.6722 | 74.0 | 148 | 0.7655 | 0.6538 | | 0.6642 | 75.0 | 150 | 0.7645 | 0.6538 | | 0.6642 | 76.0 | 152 | 0.7658 | 0.6538 | | 0.6642 | 77.0 | 154 | 0.7677 | 0.6538 | | 0.6642 | 78.0 | 156 | 0.7683 | 0.6538 | | 0.6642 | 79.0 | 158 | 0.7684 | 0.6538 | | 0.6491 | 80.0 | 160 | 0.7686 | 0.6538 | ### Framework versions - Transformers 4.36.2 - Pytorch 2.1.2+cu118 - Datasets 2.16.1 - Tokenizers 0.15.0

tgama/wem_sentiment_model_v2

tgama

"2024-06-20T18:03:20Z"

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

"2024-06-16T21:00:04Z"

--- 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:** tgama - **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)

Auart/klm

Auart

"2024-06-23T10:21:47Z"

0

null

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

null

"2024-06-16T21:00:05Z"

--- license: openrail ---

pascal-maker/paligemma_vqav2

pascal-maker

"2024-06-16T21:01:39Z"

0

null

[ "region:us" ]

null

"2024-06-16T21:01:39Z"

Entry not found

BIFOLD-BigEarthNetv2-0/BENv2-resnet101-all-v0.1.1

BIFOLD-BigEarthNetv2-0

"2024-06-19T14:50:42Z"

0

transformers

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

null

"2024-06-16T21:03:12Z"

--- tags: - model_hub_mixin - pytorch_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]

BIFOLD-BigEarthNetv2-0/BENv2-mixer_b16_224-all-v0.1.1

BIFOLD-BigEarthNetv2-0

"2024-06-19T15:10:19Z"

0

transformers

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

null

"2024-06-16T21:03:54Z"

--- tags: - model_hub_mixin - pytorch_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]

Avalonus/Griffith

Avalonus

"2024-06-16T21:42:58Z"

0

null

[ "region:us" ]

null

"2024-06-16T21:04:52Z"

Entry not found

Edgar404/donut-shivi-cheques_pruning_0.5

Edgar404

"2024-06-19T22:57:12Z"

0

transformers

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

null

"2024-06-16T21:07:44Z"

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

Augusto777/vit-base-patch16-224-dmae-TS

Augusto777

"2024-06-16T21:42:04Z"

0

transformers

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

image-classification

"2024-06-16T21:07:55Z"

Entry not found

liminerity/duck-unsloth.F16.gguf

liminerity

"2024-06-16T21:08:31Z"

0

transformers

[ "transformers", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:liminerity/m7-64-bitnet-alpaca-1", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

"2024-06-16T21:08:30Z"

--- language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl base_model: liminerity/m7-64-bitnet-alpaca-1 --- # Uploaded model - **Developed by:** liminerity - **License:** apache-2.0 - **Finetuned from model :** liminerity/m7-64-bitnet-alpaca-1 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)

Augusto777/swinv2-tiny-patch4-window8-256-ve-UH2

Augusto777

"2024-06-16T21:16:56Z"

0

transformers

[ "transformers", "tensorboard", "safetensors", "swinv2", "image-classification", "generated_from_trainer", "base_model:microsoft/swinv2-tiny-patch4-window8-256", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

"2024-06-16T21:08:49Z"

--- license: apache-2.0 base_model: microsoft/swinv2-tiny-patch4-window8-256 tags: - generated_from_trainer metrics: - accuracy model-index: - name: swinv2-tiny-patch4-window8-256-ve-UH2 results: [] ---  # swinv2-tiny-patch4-window8-256-ve-UH2 This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.7448 - Accuracy: 0.7308 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 80 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 2 | 1.6091 | 0.4038 | | No log | 2.0 | 4 | 1.6070 | 0.4231 | | No log | 3.0 | 6 | 1.6017 | 0.4038 | | No log | 4.0 | 8 | 1.5911 | 0.4038 | | 1.6022 | 5.0 | 10 | 1.5707 | 0.4038 | | 1.6022 | 6.0 | 12 | 1.5355 | 0.4038 | | 1.6022 | 7.0 | 14 | 1.4951 | 0.4038 | | 1.6022 | 8.0 | 16 | 1.4528 | 0.4038 | | 1.6022 | 9.0 | 18 | 1.4096 | 0.4038 | | 1.4645 | 10.0 | 20 | 1.3820 | 0.4038 | | 1.4645 | 11.0 | 22 | 1.4055 | 0.4038 | | 1.4645 | 12.0 | 24 | 1.3765 | 0.4038 | | 1.4645 | 13.0 | 26 | 1.3820 | 0.4038 | | 1.4645 | 14.0 | 28 | 1.3712 | 0.4038 | | 1.3172 | 15.0 | 30 | 1.3546 | 0.4038 | | 1.3172 | 16.0 | 32 | 1.3637 | 0.4038 | | 1.3172 | 17.0 | 34 | 1.3646 | 0.4038 | | 1.3172 | 18.0 | 36 | 1.3271 | 0.4038 | | 1.3172 | 19.0 | 38 | 1.3084 | 0.4038 | | 1.2549 | 20.0 | 40 | 1.3402 | 0.4038 | | 1.2549 | 21.0 | 42 | 1.3550 | 0.4038 | | 1.2549 | 22.0 | 44 | 1.2677 | 0.4038 | | 1.2549 | 23.0 | 46 | 1.2093 | 0.4038 | | 1.2549 | 24.0 | 48 | 1.2040 | 0.4231 | | 1.2092 | 25.0 | 50 | 1.2963 | 0.4231 | | 1.2092 | 26.0 | 52 | 1.2917 | 0.4808 | | 1.2092 | 27.0 | 54 | 1.1798 | 0.5769 | | 1.2092 | 28.0 | 56 | 1.1047 | 0.6346 | | 1.2092 | 29.0 | 58 | 1.0923 | 0.6731 | | 1.1321 | 30.0 | 60 | 1.1066 | 0.6538 | | 1.1321 | 31.0 | 62 | 1.0874 | 0.6538 | | 1.1321 | 32.0 | 64 | 1.0548 | 0.6731 | | 1.1321 | 33.0 | 66 | 1.0012 | 0.6538 | | 1.1321 | 34.0 | 68 | 0.9641 | 0.6923 | | 1.0022 | 35.0 | 70 | 0.9796 | 0.6538 | | 1.0022 | 36.0 | 72 | 0.9631 | 0.6538 | | 1.0022 | 37.0 | 74 | 0.9040 | 0.6731 | | 1.0022 | 38.0 | 76 | 0.8731 | 0.6923 | | 1.0022 | 39.0 | 78 | 0.8960 | 0.6731 | | 0.8941 | 40.0 | 80 | 0.9133 | 0.6538 | | 0.8941 | 41.0 | 82 | 0.8507 | 0.6923 | | 0.8941 | 42.0 | 84 | 0.8064 | 0.7115 | | 0.8941 | 43.0 | 86 | 0.8075 | 0.7115 | | 0.8941 | 44.0 | 88 | 0.8486 | 0.6923 | | 0.7866 | 45.0 | 90 | 0.8075 | 0.6923 | | 0.7866 | 46.0 | 92 | 0.7496 | 0.6731 | | 0.7866 | 47.0 | 94 | 0.7431 | 0.6731 | | 0.7866 | 48.0 | 96 | 0.7442 | 0.6731 | | 0.7866 | 49.0 | 98 | 0.7735 | 0.6923 | | 0.7281 | 50.0 | 100 | 0.7751 | 0.6923 | | 0.7281 | 51.0 | 102 | 0.7370 | 0.6923 | | 0.7281 | 52.0 | 104 | 0.7230 | 0.6923 | | 0.7281 | 53.0 | 106 | 0.7314 | 0.6923 | | 0.7281 | 54.0 | 108 | 0.7498 | 0.6731 | | 0.6725 | 55.0 | 110 | 0.7557 | 0.6731 | | 0.6725 | 56.0 | 112 | 0.7314 | 0.7115 | | 0.6725 | 57.0 | 114 | 0.7334 | 0.7115 | | 0.6725 | 58.0 | 116 | 0.7375 | 0.7115 | | 0.6725 | 59.0 | 118 | 0.7434 | 0.6923 | | 0.6526 | 60.0 | 120 | 0.7548 | 0.6731 | | 0.6526 | 61.0 | 122 | 0.7813 | 0.7115 | | 0.6526 | 62.0 | 124 | 0.7722 | 0.6923 | | 0.6526 | 63.0 | 126 | 0.7469 | 0.6923 | | 0.6526 | 64.0 | 128 | 0.7402 | 0.6731 | | 0.5915 | 65.0 | 130 | 0.7448 | 0.7308 | | 0.5915 | 66.0 | 132 | 0.7467 | 0.6923 | | 0.5915 | 67.0 | 134 | 0.7496 | 0.6731 | | 0.5915 | 68.0 | 136 | 0.7518 | 0.7308 | | 0.5915 | 69.0 | 138 | 0.7453 | 0.7115 | | 0.578 | 70.0 | 140 | 0.7385 | 0.6923 | | 0.578 | 71.0 | 142 | 0.7411 | 0.6731 | | 0.578 | 72.0 | 144 | 0.7442 | 0.6731 | | 0.578 | 73.0 | 146 | 0.7440 | 0.6731 | | 0.578 | 74.0 | 148 | 0.7428 | 0.6923 | | 0.5826 | 75.0 | 150 | 0.7414 | 0.6923 | | 0.5826 | 76.0 | 152 | 0.7416 | 0.6923 | | 0.5826 | 77.0 | 154 | 0.7414 | 0.6923 | | 0.5826 | 78.0 | 156 | 0.7413 | 0.6731 | | 0.5826 | 79.0 | 158 | 0.7413 | 0.6731 | | 0.5586 | 80.0 | 160 | 0.7415 | 0.6923 | ### Framework versions - Transformers 4.36.2 - Pytorch 2.1.2+cu118 - Datasets 2.16.1 - Tokenizers 0.15.0

RichardErkhov/mlabonne_-_Daredevil-8B-abliterated-gguf

RichardErkhov

"2024-06-16T21:09:38Z"

0

null

[ "region:us" ]

null

"2024-06-16T21:09:38Z"

Entry not found

Dani3lRg/sentiment-analysis-distilbert

Dani3lRg

"2024-06-16T21:09:44Z"

0

null

[ "region:us" ]

null

"2024-06-16T21:09:44Z"

Entry not found

RichardErkhov/Toten5_-_Marcoroni-neural-chat-7B-v2-gguf

RichardErkhov

"2024-06-16T21:10:08Z"

0

null

[ "region:us" ]

null

"2024-06-16T21:10:08Z"

Entry not found

AriaRahmati1/222shesmat2

AriaRahmati1

"2024-06-16T23:00:59Z"

0

null

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

null

"2024-06-16T21:12:19Z"

--- license: openrail ---