librarian-bots/model_cards_with_metadata_test

modelId stringlengths 5 122	author stringlengths 2 42	last_modified timestamp[us, tz=UTC]	likes int64 0 11k	library_name stringclasses 245 values	tags listlengths 1 4.05k	pipeline_tag stringclasses 48 values	createdAt timestamp[us, tz=UTC]	card stringlengths 1 901k
starnet/04-star-06-28-01	starnet	2024-06-27T23:32:38Z	0	transformers	[ "transformers", "safetensors", "stablelm", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-06-27T23:29:47Z	Entry not found
kvankirk/test_repo	kvankirk	2024-06-27T23:30:42Z	0	null	[ "region:us" ]	null	2024-06-27T23:30:42Z	Entry not found
ABDALLALSWAITI/3d-icon-SDXL-LoRA	ABDALLALSWAITI	2024-06-27T23:31:20Z	0	null	[ "region:us" ]	null	2024-06-27T23:31:20Z	Entry not found
ycfNTU/B_anger_lora_llama7b	ycfNTU	2024-06-27T23:33:07Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T23:32:58Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Sushant0809/BERT-NER-MODEL-G1-MEDICAL	Sushant0809	2024-06-28T06:46:27Z	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T23:33:41Z	--- 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]
habulaj/6998955215	habulaj	2024-06-27T23:34:16Z	0	null	[ "region:us" ]	null	2024-06-27T23:34:09Z	Entry not found
mpa21/m	mpa21	2024-06-27T23:35:52Z	0	null	[ "license:openrail", "region:us" ]	null	2024-06-27T23:35:24Z	--- license: openrail ---
pinguG/MrFall	pinguG	2024-06-27T23:40:37Z	0	null	[ "region:us" ]	null	2024-06-27T23:39:54Z	Entry not found
habulaj/468329438147	habulaj	2024-06-27T23:41:02Z	0	null	[ "region:us" ]	null	2024-06-27T23:40:52Z	Entry not found
Adoresever/Qwen2-0.5B-Instruct	Adoresever	2024-06-27T23:44:33Z	0	transformers	[ "transformers", "text-generation-inference", "unsloth", "qwen2", "gguf", "en", "base_model:unsloth/qwen2-0.5b-instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T23:44:31Z	--- base_model: unsloth/qwen2-0.5b-instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - qwen2 - gguf --- # Uploaded model - Developed by: Adoresever - License: apache-2.0 - Finetuned from model : unsloth/qwen2-0.5b-instruct-bnb-4bit This qwen2 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)
markim/dae-llama3-adapter	markim	2024-06-27T23:48:22Z	0	null	[ "safetensors", "license:apache-2.0", "region:us" ]	null	2024-06-27T23:44:52Z	--- license: apache-2.0 ---
faissalb/cih_lora_llama	faissalb	2024-06-27T23:53:58Z	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	2024-06-27T23:53:43Z	--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: faissalb - 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)
EthanRhys/Ariem	EthanRhys	2024-06-27T23:57:12Z	0	null	[ "license:openrail++", "region:us" ]	null	2024-06-27T23:55:46Z	--- license: openrail++ ---
Xrunner/dpo-juggernautxl	Xrunner	2024-06-28T00:01:42Z	0	null	[ "region:us" ]	null	2024-06-28T00:01:24Z	Entry not found
starnet/16-star-06-28-01	starnet	2024-06-28T00:08:37Z	0	transformers	[ "transformers", "safetensors", "stablelm", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-06-28T00:05:26Z	Entry not found
scano2171/Asistente	scano2171	2024-06-28T00:06:51Z	0	null	[ "license:cc-by-nc-2.0", "region:us" ]	null	2024-06-28T00:06:51Z	--- license: cc-by-nc-2.0 ---
habulaj/171778147485	habulaj	2024-06-28T00:10:59Z	0	null	[ "region:us" ]	null	2024-06-28T00:10:54Z	Entry not found
habulaj/1654216299	habulaj	2024-06-28T00:13:47Z	0	null	[ "region:us" ]	null	2024-06-28T00:13:39Z	Entry not found
abdiharyadi/indoamrbart-mbart-triple-ft-parser-no-nst-64-eps	abdiharyadi	2024-06-28T00:22:27Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-28T00:20:38Z	Entry not found
WilAI/gpt-neo-x-1.3b-qlora-test	WilAI	2024-06-28T00:21:15Z	1	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T00:21:13Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - 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]
hyungonryu/milklm	hyungonryu	2024-06-28T01:59:54Z	0	null	[ "region:us" ]	null	2024-06-28T00:22:06Z	Entry not found
tctrautman/20240627-kibbe-prod-flattened-celeb-data-3x	tctrautman	2024-06-28T00:25:09Z	0	null	[ "safetensors", "generated_from_trainer", "base_model:HuggingFaceM4/idefics2-8b", "license:apache-2.0", "region:us" ]	null	2024-06-28T00:25:06Z	--- license: apache-2.0 base_model: HuggingFaceM4/idefics2-8b tags: - generated_from_trainer model-index: - name: 20240627-kibbe-prod-flattened-celeb-data-3x 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/dubs/Kibbe-Prod/runs/e70lt24a) # 20240627-kibbe-prod-flattened-celeb-data-3x This model is a fine-tuned version of [HuggingFaceM4/idefics2-8b](https://huggingface.co/HuggingFaceM4/idefics2-8b) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0319 ## 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: 1 - eval_batch_size: 1 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:---------------:\| \| 0.4524 \| 0.5 \| 675 \| 0.0399 \| \| 0.3479 \| 1.0 \| 1350 \| 0.0364 \| \| 0.8157 \| 1.5 \| 2025 \| 0.0340 \| \| 0.6013 \| 2.0 \| 2700 \| 0.0319 \| ### Framework versions - Transformers 4.43.0.dev0 - Pytorch 2.1.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1
habulaj/5574342616	habulaj	2024-06-28T00:25:59Z	0	null	[ "region:us" ]	null	2024-06-28T00:25:53Z	Entry not found
habulaj/6216146721	habulaj	2024-06-28T00:27:07Z	0	null	[ "region:us" ]	null	2024-06-28T00:26:59Z	Entry not found
roberto2467/titanic_model	roberto2467	2024-06-28T00:41:24Z	0	null	[ "region:us" ]	null	2024-06-28T00:27:02Z	Entry not found
testje11/myllama	testje11	2024-06-28T00:32:10Z	0	transformers	[ "transformers", "safetensors", "unsloth", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T00:27:32Z	--- library_name: transformers tags: - unsloth --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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]
habulaj/547747993	habulaj	2024-06-28T00:29:05Z	0	null	[ "region:us" ]	null	2024-06-28T00:28:55Z	Entry not found
Ahmad-11/crash_expert200_ck390	Ahmad-11	2024-06-28T00:36:02Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T00:35:58Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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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]
cccornflake/absa_v2_entity	cccornflake	2024-06-28T00:39:43Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T00:39:43Z	--- license: apache-2.0 ---
habulaj/483264454062	habulaj	2024-06-28T00:40:30Z	0	null	[ "region:us" ]	null	2024-06-28T00:40:09Z	Entry not found
habulaj/483827454651	habulaj	2024-06-28T00:44:18Z	0	null	[ "region:us" ]	null	2024-06-28T00:43:59Z	Entry not found
srbdtwentyfour/mystery-llama-3-8b-v8	srbdtwentyfour	2024-06-28T15:26:29Z	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	2024-06-28T00:46:56Z	--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: srbdtwentyfour - 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)
habulaj/217432189703	habulaj	2024-06-28T00:47:26Z	0	null	[ "region:us" ]	null	2024-06-28T00:47:18Z	Entry not found
habulaj/349158492932	habulaj	2024-06-28T00:51:03Z	0	null	[ "region:us" ]	null	2024-06-28T00:50:52Z	Entry not found
N00203979/Pregunta1	N00203979	2024-06-28T00:52:07Z	0	null	[ "region:us" ]	null	2024-06-28T00:51:17Z	Entry not found
testje11/myopenchat	testje11	2024-06-28T00:52:11Z	0	transformers	[ "transformers", "safetensors", "unsloth", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T00:51:35Z	--- 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. 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More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
caenopy/music-medium-800k-mlc-q0f16	caenopy	2024-06-28T00:53:37Z	0	null	[ "region:us" ]	null	2024-06-28T00:52:52Z	Entry not found
rulerpe/code-search-net-tokenizer	rulerpe	2024-06-28T00:54:25Z	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T00:54:25Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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]
debased-ai/llama-3-tweaks	debased-ai	2024-06-28T01:10:17Z	0	null	[ "license:llama3", "region:us" ]	null	2024-06-28T01:01:02Z	--- license: llama3 --- This repo currently contains the version of generation_config.json from Llama 3 8B Instruct that declares both 128001 and 128009 to be eos tokens. This file can be used to "repair" both full weight models and exl2 quants thereto. Just drop a copy of the file in the same directory as the safetensors files.
Arodrigo/temp003	Arodrigo	2024-06-28T01:05:53Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T01:05:51Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
ghzno1/diffusion	ghzno1	2024-06-28T01:09:28Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T01:08:49Z	--- license: apache-2.0 ---
fc91/phi3-mini-instruct-full_ethics-lora	fc91	2024-06-28T16:08:35Z	0	transformers	[ "transformers", "safetensors", "dataset:hendrycks/ethics", "arxiv:1910.09700", "license:cc-by-4.0", "endpoints_compatible", "region:us" ]	null	2024-06-28T01:09:22Z	--- library_name: transformers license: cc-by-4.0 datasets: - hendrycks/ethics --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> Fine-tuned version of Phi-3-mini-4k-instruct on a subset of the hendrycks/ethics dataset <!-- ## 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. ```markdown from transformers import AutoModel model = AutoModel.from_pretrained("fc91/phi3-mini-instruct-full_ethics-lora") tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct") ``` ## 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. --> ["hendrycks/ethics"](https://huggingface.co/datasets/hendrycks/ethics) ```markdown The following subsets of the above dataset were leveraged: -commonsense (10k random samples) -deontology (10k random samples) -justice (10k random samples) -utilitarianism (10k random samples) ``` ### 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 ```markdown per_device_train_batch_size=16 per_device_eval_batch_size=32 gradient_accumulation_steps=2 gradient_checkpointing=True warmup_steps=100 num_train_epochs=1 learning_rate=0.00005 weight_decay=0.01 optim="adamw_hf" fp16=True ``` #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> The overall training took 3 hours and 23 minutes. ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> Training Loss = 0.181700 Validation Loss = 0.119734 ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> ["hendrycks/ethics"](https://huggingface.co/datasets/hendrycks/ethics) ```markdown The following subsets of the above dataset were leveraged: -commonsense (2.5k random samples) -deontology (2.5k random samples) -justice (2.5k random samples) -utilitarianism (2.5k random samples) ``` #### 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 NVIDIA A100-SXM4-40GB #### 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]
alexjx1/comfyui-models	alexjx1	2024-06-28T01:16:30Z	0	null	[ "region:us" ]	null	2024-06-28T01:12:32Z	Entry not found
roberto2467/arbol_decision	roberto2467	2024-06-28T01:17:05Z	0	null	[ "region:us" ]	null	2024-06-28T01:16:41Z	Entry not found
N00203979/Pregunta5_Arbol	N00203979	2024-06-28T01:21:09Z	0	null	[ "region:us" ]	null	2024-06-28T01:19:35Z	Entry not found
katt1234546/katty	katt1234546	2024-06-28T01:23:25Z	0	null	[ "region:us" ]	null	2024-06-28T01:23:25Z	Entry not found
nautroi/LocalClimaX	nautroi	2024-06-28T09:14:40Z	0	null	[ "license:unknown", "region:us" ]	null	2024-06-28T01:23:27Z	--- license: unknown ---
AdamKasumovic/llama3-8b-instruct-bactrian-x-xh-100-percent-low-high-perplexity	AdamKasumovic	2024-06-28T01:27:40Z	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "text-generation-inference", "unsloth", "trl", "conversational", "en", "base_model:unsloth/llama-3-8b-Instruct-bnb-4bit", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-06-28T01:23:48Z	--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: AdamKasumovic - License: apache-2.0 - Finetuned from model : unsloth/llama-3-8b-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)
LalMani/ddpm-furniture	LalMani	2024-06-28T01:24:48Z	0	null	[ "region:us" ]	null	2024-06-28T01:24:48Z	Entry not found
tb1211/finetuning-sentiment-model-3000-samples	tb1211	2024-06-28T01:27:06Z	0	null	[ "region:us" ]	null	2024-06-28T01:27:01Z	Entry not found
uooogh/lpw_stable_diffusion_xl	uooogh	2024-06-28T01:31:44Z	0	null	[ "region:us" ]	null	2024-06-28T01:28:50Z	Entry not found
metheistos/MT	metheistos	2024-06-28T01:30:46Z	0	null	[ "license:gpl-2.0", "region:us" ]	null	2024-06-28T01:30:46Z	--- license: gpl-2.0 ---
AniaAri/trabajo	AniaAri	2024-06-28T01:46:06Z	0	null	[ "region:us" ]	null	2024-06-28T01:34:36Z	Entry not found
chenqitao/swintransformer	chenqitao	2024-06-28T01:38:24Z	0	null	[ "region:us" ]	null	2024-06-28T01:38:24Z	Entry not found
LeonOuO/distilbert-base-uncased-finetuned-section	LeonOuO	2024-07-02T09:11:42Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-06-28T01:40:24Z	Entry not found
Hyungmo/testModel	Hyungmo	2024-06-28T01:40:52Z	0	null	[ "license:gemma", "region:us" ]	null	2024-06-28T01:40:52Z	--- license: gemma ---
habulaj/100435337994	habulaj	2024-06-28T01:41:06Z	0	null	[ "region:us" ]	null	2024-06-28T01:41:03Z	Entry not found
habulaj/2599527171	habulaj	2024-06-28T01:43:39Z	0	null	[ "region:us" ]	null	2024-06-28T01:43:32Z	Entry not found
vbv373/text2struc_allstruc_allop_uncom_codegen_0627-outputs	vbv373	2024-06-30T11:32:24Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-28T01:43:43Z	Entry not found
TensorStack/stable-diffusion-3-lite-onnx	TensorStack	2024-06-28T02:01:57Z	0	null	[ "onnx", "text-to-image", "region:us" ]	text-to-image	2024-06-28T01:44:31Z	--- pipeline_tag: text-to-image --- # Stable-Diffusion 3 Lite ## Original Model https://huggingface.co/stabilityai/stable-diffusion-3-medium ### This conversion does not include the T5 models so is defined as "lite" not "medium" ## C# Inference Demo https://github.com/TensorStack-AI/OnnxStack ```csharp // Create Pipeline var pipeline = StableDiffusion3Pipeline.CreatePipeline("D:\\Models\\stable-diffusion-3-lite-onnx"); // Prompt var promptOptions = new PromptOptions { Prompt = "A cat holding a sign that says OnnxStack Stable Diffusion 3" }; // Run pipeline var result = await pipeline.GenerateImageAsync(promptOptions); // Save Image Result await result.SaveAsync("Result.png"); ``` ## Inference Result ![Intro Image](Sample.png)
Arodrigo/temp004	Arodrigo	2024-06-28T01:45:31Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T01:45:29Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
ashprengel/outputs_mistral_b_finance_finetuned_test	ashprengel	2024-06-28T02:03:44Z	0	null	[ "tensorboard", "safetensors", "region:us" ]	null	2024-06-28T01:48:24Z	Entry not found
chenqitao/swinb	chenqitao	2024-06-28T01:53:32Z	0	null	[ "region:us" ]	null	2024-06-28T01:51:38Z	import torch import torch.nn as nn import torch.optim as optim from torchvision import datasets, transforms, models from sklearn.metrics import confusion_matrix, roc_curve, auc, accuracy_score, ConfusionMatrixDisplay import os import numpy as np import matplotlib.pyplot as plt from torchvision.datasets import ImageFolder # 数据路径 train_data_dir = "/root/autodl-tmp/vqvaeboi/train" val_data_dir = '/root/autodl-tmp/vqvaeboi/test' best_accuracy = 0.0 # 数据预处理和加载 data_transform = transforms.Compose([ transforms.RandomResizedCrop(224), transforms.RandomHorizontalFlip(), # 随机水平翻转 transforms.ColorJitter(brightness=0.2, contrast=0.2, saturation=0.2, hue=0.1), # 随机颜色抖动 transforms.RandomRotation(degrees=15), # 随机旋转 transforms.ToTensor(), # This should come before Normalize transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), # This should be after ToTensor ]) train_dataset: ImageFolder = datasets.ImageFolder(root=train_data_dir, transform=data_transform) val_dataset = datasets.ImageFolder(root=val_data_dir, transform=data_transform) dataloaders = { 'train': torch.utils.data.DataLoader(train_dataset, batch_size=32, shuffle=True, num_workers=4), 'val': torch.utils.data.DataLoader(val_dataset, batch_size=32, shuffle=False, num_workers=4), } # ResNet-18 模型定义 model = models.swin_b(pretrained=True) num_ftrs = model.head.in_features # 获取最后一个线性层输入的特征数量 model.head = nn.Linear(num_ftrs, 2) # 创建一个新的线性层，输出特征维度为 2 # 损失函数和优化器 criterion = nn.CrossEntropyLoss() optimizer = optim.SGD(model.parameters(), lr=0.0001) # 将模型和数据移动到GPU上 num_epochs = 100 device = torch.device("cuda" if torch.cuda.is_available() else "cpu") model = model.to(device) train_losses = [] val_losses = [] train_accuracies = [] val_accuracies = [] best_val_labels = [] best_val_preds = [] for epoch in range(num_epochs): for phase in ['train', 'val']: if phase == 'train': model.train() else: model.eval() running_loss = 0.0 running_corrects = 0 all_labels = [] all_preds = [] for inputs, labels in dataloaders[phase]: inputs, labels = inputs.to(device), labels.to(device) optimizer.zero_grad() with torch.set_grad_enabled(phase == 'train'): outputs = model(inputs) loss = criterion(outputs, labels) if phase == 'train': loss.backward() optimizer.step() running_loss += loss.item() * inputs.size(0) _, preds = torch.max(outputs, 1) running_corrects += torch.sum(preds == labels.data) if phase == 'val': all_labels.extend(labels.cpu().numpy()) all_preds.extend(preds.cpu().numpy()) epoch_loss = running_loss / len(dataloaders[phase].dataset) epoch_acc = running_corrects.double() / len(dataloaders[phase].dataset) print(f'Epoch {epoch}/{num_epochs} \| {phase} \| Loss: {epoch_loss:.4f} \| Acc: {epoch_acc:.4f}') if phase == 'train': train_losses.append(epoch_loss) train_accuracies.append(epoch_acc) else: val_losses.append(epoch_loss) val_accuracies.append(epoch_acc) if epoch_acc > best_accuracy: best_accuracy = epoch_acc torch.save(model.state_dict(), 'best_model.pth') best_val_labels = all_labels best_val_preds = all_preds # 加载最佳模型参数 model.load_state_dict(torch.load('best_model.pth')) # 可视化部分... # 绘制 Loss 曲线图 plt.figure(figsize=(10, 5)) plt.plot(train_losses, label='Training Loss') plt.plot(val_losses, label='Validation Loss') plt.xlabel('Epochs') plt.ylabel('Loss') plt.title('Training and Validation Loss') plt.legend() plt.show() # 绘制 Accuracy 曲线图 plt.figure(figsize=(10, 5)) plt.plot(train_accuracies, label='Training Accuracy') plt.plot(val_accuracies, label='Validation Accuracy') plt.xlabel('Epochs') plt.ylabel('Accuracy') plt.title('Training and Validation Accuracy') plt.legend() plt.show() # 使用 best_val_labels 和 best_val_preds 来计算混淆矩阵 conf_matrix = confusion_matrix(best_val_labels, best_val_preds) print("Confusion Matrix:") print(conf_matrix) # 绘制混淆矩阵图 class_names = sorted(train_dataset.classes) disp = ConfusionMatrixDisplay(confusion_matrix=conf_matrix, display_labels=class_names) disp.plot(cmap='Blues', values_format='d') plt.title('Confusion Matrix') plt.show() # 计算 ROC 曲线和 AUC fpr, tpr, _ = roc_curve(best_val_labels, best_val_preds) roc_auc = auc(fpr, tpr) # 首先计算混淆矩阵 conf_matrix = confusion_matrix(best_val_labels, best_val_preds) # 对于二分类，混淆矩阵布局如下： # TN FP # FN TP TN, FP, FN, TP = conf_matrix.ravel() # 计算特异度和灵敏度 Specificity = TN / (TN + FP) Sensitivity = TP / (TP + FN) print(f'Specificity: {Specificity:.4f}') print(f'Sensitivity: {Sensitivity:.4f}') # 绘制 ROC 曲线 plt.figure(figsize=(8, 8)) plt.plot(fpr, tpr, color='darkorange', lw=2, label=f'AUC = {roc_auc:.2f}') plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--') plt.xlim([0.0, 1.0]) plt.ylim([0.0, 1.05]) plt.xlabel('False Positive Rate') plt.ylabel('True Positive Rate') plt.title('Receiver Operating Characteristic') plt.legend(loc="lower right") plt.show() # 输出最佳准确度 print(f'Best Validation Accuracy: {best_accuracy:.4f}')
guialfaro/gemma-2-9b-it-pytorch-awq	guialfaro	2024-06-28T01:53:34Z	0	null	[ "license:gemma", "region:us" ]	null	2024-06-28T01:53:34Z	--- license: gemma ---
LuuNgoc2k2/ViNER-MDeberta	LuuNgoc2k2	2024-06-28T01:59:23Z	0	null	[ "pytorch", "region:us" ]	null	2024-06-28T01:57:58Z	Entry not found
chrisliu298/tofu_forget01_classifier	chrisliu298	2024-06-28T02:10:32Z	0	transformers	[ "transformers", "safetensors", "roberta", "text-classification", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-06-28T02:08:52Z	--- library_name: transformers tags: [] --- A `roberta-base` classifier that classifies if a prompt belongs to the `forget01` split of the [TOFU dataset](https://huggingface.co/datasets/locuslab/TOFU).
AdamKasumovic/llama3-8b-instruct-bactrian-x-af-100-percent-med-high-perplexity	AdamKasumovic	2024-06-28T02:09:43Z	0	transformers	[ "transformers", "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	2024-06-28T02:09:43Z	--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: AdamKasumovic - License: apache-2.0 - Finetuned from model : unsloth/llama-3-8b-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)
abdiharyadi/indoamrbart-mbart-triple-ft-parser-no-nst-128-eps	abdiharyadi	2024-06-28T02:12:52Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-28T02:10:40Z	Entry not found
ashprengel/mistral_b_finance_finetuned_test	ashprengel	2024-06-28T02:10:55Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T02:10:44Z	--- 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]
Anujgr8/wav2vec2-base-Gujraati-large-4.5	Anujgr8	2024-06-28T02:52:51Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "wav2vec2", "automatic-speech-recognition", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2024-06-28T02:10:45Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
KYUNGHYUN9/itos_v0.003_1.3b-1000step_longdata	KYUNGHYUN9	2024-06-28T02:12:43Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T02:12:39Z	--- 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]
Jaqueline26/Imdimaq	Jaqueline26	2024-06-28T02:13:21Z	0	null	[ "region:us" ]	null	2024-06-28T02:13:21Z	Entry not found
NamHunter99/namzephyr-7b-lora-4bit	NamHunter99	2024-06-28T02:18:51Z	0	null	[ "safetensors", "license:apache-2.0", "region:us" ]	null	2024-06-28T02:16:18Z	--- license: apache-2.0 ---
patie/bert-finetuned-squad	patie	2024-06-28T02:17:48Z	0	null	[ "region:us" ]	null	2024-06-28T02:17:48Z	Entry not found
thesven/Aether-Code-Mistral-7B-0.3-v1-4bit-adapter	thesven	2024-06-28T02:19:07Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:unsloth/mistral-7b-v0.3-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-28T02:18:14Z	--- base_model: unsloth/mistral-7b-v0.3-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - Developed by: thesven - License: apache-2.0 - Finetuned from model : unsloth/mistral-7b-v0.3-bnb-4bit This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
chaewoners/HanJisungOfStrayKids	chaewoners	2024-06-28T02:22:19Z	0	null	[ "license:unknown", "region:us" ]	null	2024-06-28T02:21:56Z	--- license: unknown ---
oranchatbot/Oran	oranchatbot	2024-06-28T02:24:03Z	0	null	[ "region:us" ]	null	2024-06-28T02:24:03Z	Entry not found
Arodrigo/temp005	Arodrigo	2024-06-28T02:24:36Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T02:24:30Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
OceanandWild/Ocean	OceanandWild	2024-06-28T02:27:52Z	0	null	[ "license:mit", "region:us" ]	null	2024-06-28T02:27:52Z	--- license: mit ---
Elagra/UPN	Elagra	2024-06-28T02:29:36Z	0	null	[ "license:other", "region:us" ]	null	2024-06-28T02:29:36Z	--- license: other license_name: python license_link: LICENSE ---
SD2000/example-model	SD2000	2024-06-28T16:39:36Z	0	null	[ "region:us" ]	null	2024-06-28T02:31:04Z	# Example Model This is a model card README --- license: mit ---
Elagra/alex_upn	Elagra	2024-06-28T02:31:40Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:31:40Z	--- license: apache-2.0 ---
fabriziofalcon26/docs	fabriziofalcon26	2024-06-28T03:03:11Z	0	null	[ "region:us" ]	null	2024-06-28T02:32:16Z	Entry not found
Arodrigo/temp007	Arodrigo	2024-06-28T02:37:14Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-28T02:37:09Z	--- 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]
Skeptical-Chafferer/code-llama-7b-text-to-sql	Skeptical-Chafferer	2024-06-28T02:53:59Z	0	null	[ "tensorboard", "safetensors", "region:us" ]	null	2024-06-28T02:42:09Z	Entry not found
Bart0522/test0628	Bart0522	2024-06-28T02:44:12Z	0	null	[ "license:bsl-1.0", "region:us" ]	null	2024-06-28T02:44:12Z	--- license: bsl-1.0 ---
nam194/qwen2-7b-qlora-testcasegen-unsloth	nam194	2024-06-28T02:44:38Z	0	null	[ "region:us" ]	null	2024-06-28T02:44:38Z	Entry not found
tino123j/tcp2023	tino123j	2024-06-28T02:45:49Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:45:49Z	--- license: apache-2.0 ---
setoutlas/tcp2023	setoutlas	2024-06-28T02:46:00Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:46:00Z	--- license: apache-2.0 ---
guramiwei/tcp2023	guramiwei	2024-06-28T02:46:13Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:46:13Z	--- license: apache-2.0 ---
Roxas22/tcp2023	Roxas22	2024-06-28T02:46:54Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:46:54Z	--- license: apache-2.0 ---
GloryKuo/tcp2023	GloryKuo	2024-06-28T02:47:13Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:47:13Z	--- license: apache-2.0 ---
HanYeh/tcp2023	HanYeh	2024-06-28T02:47:39Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:47:39Z	--- license: apache-2.0 ---
AdamKasumovic/llama3-8b-instruct-bactrian-x-en-100-percent-low-perplexity	AdamKasumovic	2024-06-28T02:47:42Z	0	transformers	[ "transformers", "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	2024-06-28T02:47:41Z	--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: AdamKasumovic - License: apache-2.0 - Finetuned from model : unsloth/llama-3-8b-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)
wu561092/tcp2023	wu561092	2024-06-28T02:48:03Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:48:03Z	--- license: apache-2.0 ---
RIickMH/tcp2023	RIickMH	2024-06-28T02:48:21Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:48:21Z	--- license: apache-2.0 ---
Dormir1010/tcp2023	Dormir1010	2024-06-28T02:48:22Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:48:22Z	--- license: apache-2.0 ---
guosheng321/tcp2023	guosheng321	2024-06-28T02:48:43Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:48:43Z	--- license: apache-2.0 ---
ZChieh/tcp2023	ZChieh	2024-06-28T02:48:45Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:48:45Z	--- license: apache-2.0 ---
Dormir1010/uuu_fine_tune_gpt2	Dormir1010	2024-06-28T02:48:49Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-28T02:48:49Z	--- license: apache-2.0 ---

starnet/04-star-06-28-01

starnet

2024-06-27T23:32:38Z

0

transformers

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

text-generation

2024-06-27T23:29:47Z

Entry not found

kvankirk/test_repo

kvankirk

2024-06-27T23:30:42Z

0

null

[ "region:us" ]

null

2024-06-27T23:30:42Z

Entry not found

ABDALLALSWAITI/3d-icon-SDXL-LoRA

ABDALLALSWAITI

2024-06-27T23:31:20Z

0

null

[ "region:us" ]

null

2024-06-27T23:31:20Z

Entry not found

ycfNTU/B_anger_lora_llama7b

ycfNTU

2024-06-27T23:33:07Z

0

transformers

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

null

2024-06-27T23:32:58Z

--- 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]

Sushant0809/BERT-NER-MODEL-G1-MEDICAL

Sushant0809

2024-06-28T06:46:27Z

0

transformers

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

null

2024-06-27T23:33:41Z

--- 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]

habulaj/6998955215

habulaj

2024-06-27T23:34:16Z

0

null

[ "region:us" ]

null

2024-06-27T23:34:09Z

Entry not found

mpa21/m

mpa21

2024-06-27T23:35:52Z

0

null

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

null

2024-06-27T23:35:24Z

--- license: openrail ---

pinguG/MrFall

pinguG

2024-06-27T23:40:37Z

0

null

[ "region:us" ]

null

2024-06-27T23:39:54Z

Entry not found

habulaj/468329438147

habulaj

2024-06-27T23:41:02Z

0

null

[ "region:us" ]

null

2024-06-27T23:40:52Z

Entry not found

Adoresever/Qwen2-0.5B-Instruct

Adoresever

2024-06-27T23:44:33Z

0

transformers

[ "transformers", "text-generation-inference", "unsloth", "qwen2", "gguf", "en", "base_model:unsloth/qwen2-0.5b-instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

2024-06-27T23:44:31Z

--- base_model: unsloth/qwen2-0.5b-instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - qwen2 - gguf --- # Uploaded model - **Developed by:** Adoresever - **License:** apache-2.0 - **Finetuned from model :** unsloth/qwen2-0.5b-instruct-bnb-4bit This qwen2 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)

markim/dae-llama3-adapter

markim

2024-06-27T23:48:22Z

0

null

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

null

2024-06-27T23:44:52Z

--- license: apache-2.0 ---

faissalb/cih_lora_llama

faissalb

2024-06-27T23:53:58Z

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

2024-06-27T23:53:43Z

--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - **Developed by:** faissalb - **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)

EthanRhys/Ariem

EthanRhys

2024-06-27T23:57:12Z

0

null

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

null

2024-06-27T23:55:46Z

--- license: openrail++ ---

Xrunner/dpo-juggernautxl

Xrunner

2024-06-28T00:01:42Z

0

null

[ "region:us" ]

null

2024-06-28T00:01:24Z

Entry not found

starnet/16-star-06-28-01

starnet

2024-06-28T00:08:37Z

0

transformers

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

text-generation

2024-06-28T00:05:26Z

Entry not found

scano2171/Asistente

scano2171

2024-06-28T00:06:51Z

0

null

[ "license:cc-by-nc-2.0", "region:us" ]

null

2024-06-28T00:06:51Z

--- license: cc-by-nc-2.0 ---

habulaj/171778147485

habulaj

2024-06-28T00:10:59Z

0

null

[ "region:us" ]

null

2024-06-28T00:10:54Z

Entry not found

habulaj/1654216299

habulaj

2024-06-28T00:13:47Z

0

null

[ "region:us" ]

null

2024-06-28T00:13:39Z

Entry not found

abdiharyadi/indoamrbart-mbart-triple-ft-parser-no-nst-64-eps

abdiharyadi

2024-06-28T00:22:27Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-28T00:20:38Z

Entry not found

WilAI/gpt-neo-x-1.3b-qlora-test

WilAI

2024-06-28T00:21:15Z

0

1

transformers

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

null

2024-06-28T00:21:13Z

--- 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]

hyungonryu/milklm

hyungonryu

2024-06-28T01:59:54Z

0

null

[ "region:us" ]

null

2024-06-28T00:22:06Z

Entry not found

tctrautman/20240627-kibbe-prod-flattened-celeb-data-3x

tctrautman

2024-06-28T00:25:09Z

0

null

[ "safetensors", "generated_from_trainer", "base_model:HuggingFaceM4/idefics2-8b", "license:apache-2.0", "region:us" ]

null

2024-06-28T00:25:06Z

--- license: apache-2.0 base_model: HuggingFaceM4/idefics2-8b tags: - generated_from_trainer model-index: - name: 20240627-kibbe-prod-flattened-celeb-data-3x 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/dubs/Kibbe-Prod/runs/e70lt24a) # 20240627-kibbe-prod-flattened-celeb-data-3x This model is a fine-tuned version of [HuggingFaceM4/idefics2-8b](https://huggingface.co/HuggingFaceM4/idefics2-8b) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0319 ## 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: 1 - eval_batch_size: 1 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.4524 | 0.5 | 675 | 0.0399 | | 0.3479 | 1.0 | 1350 | 0.0364 | | 0.8157 | 1.5 | 2025 | 0.0340 | | 0.6013 | 2.0 | 2700 | 0.0319 | ### Framework versions - Transformers 4.43.0.dev0 - Pytorch 2.1.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1

habulaj/5574342616

habulaj

2024-06-28T00:25:59Z

0

null

[ "region:us" ]

null

2024-06-28T00:25:53Z

Entry not found

habulaj/6216146721

habulaj

2024-06-28T00:27:07Z

0

null

[ "region:us" ]

null

2024-06-28T00:26:59Z

Entry not found

roberto2467/titanic_model

roberto2467

2024-06-28T00:41:24Z

0

null

[ "region:us" ]

null

2024-06-28T00:27:02Z

Entry not found

testje11/myllama

testje11

2024-06-28T00:32:10Z

0

transformers

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

null

2024-06-28T00:27:32Z

--- 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]

habulaj/547747993

habulaj

2024-06-28T00:29:05Z

0

null

[ "region:us" ]

null

2024-06-28T00:28:55Z

Entry not found

Ahmad-11/crash_expert200_ck390

Ahmad-11

2024-06-28T00:36:02Z

0

transformers

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

null

2024-06-28T00:35:58Z

--- 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]

cccornflake/absa_v2_entity

cccornflake

2024-06-28T00:39:43Z

0

null

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

null

2024-06-28T00:39:43Z

--- license: apache-2.0 ---

habulaj/483264454062

habulaj

2024-06-28T00:40:30Z

0

null

[ "region:us" ]

null

2024-06-28T00:40:09Z

Entry not found

habulaj/483827454651

habulaj

2024-06-28T00:44:18Z

0

null

[ "region:us" ]

null

2024-06-28T00:43:59Z

Entry not found

srbdtwentyfour/mystery-llama-3-8b-v8

srbdtwentyfour

2024-06-28T15:26:29Z

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

2024-06-28T00:46:56Z

--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - **Developed by:** srbdtwentyfour - **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)

habulaj/217432189703

habulaj

2024-06-28T00:47:26Z

0

null

[ "region:us" ]

null

2024-06-28T00:47:18Z

Entry not found

habulaj/349158492932

habulaj

2024-06-28T00:51:03Z

0

null

[ "region:us" ]

null

2024-06-28T00:50:52Z

Entry not found

N00203979/Pregunta1

N00203979

2024-06-28T00:52:07Z

0

null

[ "region:us" ]

null

2024-06-28T00:51:17Z

Entry not found

testje11/myopenchat

testje11

2024-06-28T00:52:11Z

0

transformers

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

null

2024-06-28T00:51:35Z

--- 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]

caenopy/music-medium-800k-mlc-q0f16

caenopy

2024-06-28T00:53:37Z

0

null

[ "region:us" ]

null

2024-06-28T00:52:52Z

Entry not found

rulerpe/code-search-net-tokenizer

rulerpe

2024-06-28T00:54:25Z

0

transformers

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

null

2024-06-28T00:54:25Z

--- 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]

debased-ai/llama-3-tweaks

debased-ai

2024-06-28T01:10:17Z

0

null

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

null

2024-06-28T01:01:02Z

--- license: llama3 --- This repo currently contains the version of generation_config.json from Llama 3 8B Instruct that declares both 128001 and 128009 to be eos tokens. This file can be used to "repair" both full weight models and exl2 quants thereto. Just drop a copy of the file in the same directory as the safetensors files.

Arodrigo/temp003

Arodrigo

2024-06-28T01:05:53Z

0

transformers

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

null

2024-06-28T01:05:51Z

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

ghzno1/diffusion

ghzno1

2024-06-28T01:09:28Z

0

null

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

null

2024-06-28T01:08:49Z

--- license: apache-2.0 ---

fc91/phi3-mini-instruct-full_ethics-lora

fc91

2024-06-28T16:08:35Z

0

transformers

[ "transformers", "safetensors", "dataset:hendrycks/ethics", "arxiv:1910.09700", "license:cc-by-4.0", "endpoints_compatible", "region:us" ]

null

2024-06-28T01:09:22Z

--- library_name: transformers license: cc-by-4.0 datasets: - hendrycks/ethics --- # Model Card for Model ID  Fine-tuned version of Phi-3-mini-4k-instruct on a subset of the hendrycks/ethics dataset  ## How to Get Started with the Model Use the code below to get started with the model. ```markdown from transformers import AutoModel model = AutoModel.from_pretrained("fc91/phi3-mini-instruct-full_ethics-lora") tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct") ``` ## Training Details ### Training Data  ["hendrycks/ethics"](https://huggingface.co/datasets/hendrycks/ethics) ```markdown The following subsets of the above dataset were leveraged: -commonsense (10k random samples) -deontology (10k random samples) -justice (10k random samples) -utilitarianism (10k random samples) ``` ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters ```markdown per_device_train_batch_size=16 per_device_eval_batch_size=32 gradient_accumulation_steps=2 gradient_checkpointing=True warmup_steps=100 num_train_epochs=1 learning_rate=0.00005 weight_decay=0.01 optim="adamw_hf" fp16=True ``` #### Speeds, Sizes, Times [optional]  The overall training took 3 hours and 23 minutes. ## Evaluation  Training Loss = 0.181700 Validation Loss = 0.119734 ### Testing Data, Factors & Metrics #### Testing Data  ["hendrycks/ethics"](https://huggingface.co/datasets/hendrycks/ethics) ```markdown The following subsets of the above dataset were leveraged: -commonsense (2.5k random samples) -deontology (2.5k random samples) -justice (2.5k random samples) -utilitarianism (2.5k random samples) ``` #### 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 NVIDIA A100-SXM4-40GB #### 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]

alexjx1/comfyui-models

alexjx1

2024-06-28T01:16:30Z

0

null

[ "region:us" ]

null

2024-06-28T01:12:32Z

Entry not found

roberto2467/arbol_decision

roberto2467

2024-06-28T01:17:05Z

0

null

[ "region:us" ]

null

2024-06-28T01:16:41Z

Entry not found

N00203979/Pregunta5_Arbol

N00203979

2024-06-28T01:21:09Z

0

null

[ "region:us" ]

null

2024-06-28T01:19:35Z

Entry not found

katt1234546/katty

katt1234546

2024-06-28T01:23:25Z

0

null

[ "region:us" ]

null

2024-06-28T01:23:25Z

Entry not found

nautroi/LocalClimaX

nautroi

2024-06-28T09:14:40Z

0

null

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

null

2024-06-28T01:23:27Z

--- license: unknown ---

AdamKasumovic/llama3-8b-instruct-bactrian-x-xh-100-percent-low-high-perplexity

AdamKasumovic

2024-06-28T01:27:40Z

0

transformers

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

text-generation

2024-06-28T01:23:48Z

--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - **Developed by:** AdamKasumovic - **License:** apache-2.0 - **Finetuned from model :** unsloth/llama-3-8b-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)

LalMani/ddpm-furniture

LalMani

2024-06-28T01:24:48Z

0

null

[ "region:us" ]

null

2024-06-28T01:24:48Z

Entry not found

tb1211/finetuning-sentiment-model-3000-samples

tb1211

2024-06-28T01:27:06Z

0

null

[ "region:us" ]

null

2024-06-28T01:27:01Z

Entry not found

uooogh/lpw_stable_diffusion_xl

uooogh

2024-06-28T01:31:44Z

0

null

[ "region:us" ]

null

2024-06-28T01:28:50Z

Entry not found

metheistos/MT

metheistos

2024-06-28T01:30:46Z

0

null

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

null

2024-06-28T01:30:46Z

--- license: gpl-2.0 ---

AniaAri/trabajo

AniaAri

2024-06-28T01:46:06Z

0

null

[ "region:us" ]

null

2024-06-28T01:34:36Z

Entry not found

chenqitao/swintransformer

chenqitao

2024-06-28T01:38:24Z

0

null

[ "region:us" ]

null

2024-06-28T01:38:24Z

Entry not found

LeonOuO/distilbert-base-uncased-finetuned-section

LeonOuO

2024-07-02T09:11:42Z

0

transformers

[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-06-28T01:40:24Z

Entry not found

Hyungmo/testModel

Hyungmo

2024-06-28T01:40:52Z

0

null

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

null

2024-06-28T01:40:52Z

--- license: gemma ---

habulaj/100435337994

habulaj

2024-06-28T01:41:06Z

0

null

[ "region:us" ]

null

2024-06-28T01:41:03Z

Entry not found

habulaj/2599527171

habulaj

2024-06-28T01:43:39Z

0

null

[ "region:us" ]

null

2024-06-28T01:43:32Z

Entry not found

vbv373/text2struc_allstruc_allop_uncom_codegen_0627-outputs

vbv373

2024-06-30T11:32:24Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-28T01:43:43Z

Entry not found

TensorStack/stable-diffusion-3-lite-onnx

TensorStack

2024-06-28T02:01:57Z

0

null

[ "onnx", "text-to-image", "region:us" ]

text-to-image

2024-06-28T01:44:31Z

--- pipeline_tag: text-to-image --- # Stable-Diffusion 3 Lite ## Original Model https://huggingface.co/stabilityai/stable-diffusion-3-medium ### This conversion does not include the T5 models so is defined as "lite" not "medium" ## C# Inference Demo https://github.com/TensorStack-AI/OnnxStack ```csharp // Create Pipeline var pipeline = StableDiffusion3Pipeline.CreatePipeline("D:\\Models\\stable-diffusion-3-lite-onnx"); // Prompt var promptOptions = new PromptOptions { Prompt = "A cat holding a sign that says OnnxStack Stable Diffusion 3" }; // Run pipeline var result = await pipeline.GenerateImageAsync(promptOptions); // Save Image Result await result.SaveAsync("Result.png"); ``` ## Inference Result ![Intro Image](Sample.png)

Arodrigo/temp004

Arodrigo

2024-06-28T01:45:31Z

0

transformers

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

null

2024-06-28T01:45:29Z

--- 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]

ashprengel/outputs_mistral_b_finance_finetuned_test

ashprengel

2024-06-28T02:03:44Z

0

null

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

null

2024-06-28T01:48:24Z

Entry not found

chenqitao/swinb

chenqitao

2024-06-28T01:53:32Z

0

null

[ "region:us" ]

null

2024-06-28T01:51:38Z

import torch import torch.nn as nn import torch.optim as optim from torchvision import datasets, transforms, models from sklearn.metrics import confusion_matrix, roc_curve, auc, accuracy_score, ConfusionMatrixDisplay import os import numpy as np import matplotlib.pyplot as plt from torchvision.datasets import ImageFolder # 数据路径 train_data_dir = "/root/autodl-tmp/vqvaeboi/train" val_data_dir = '/root/autodl-tmp/vqvaeboi/test' best_accuracy = 0.0 # 数据预处理和加载 data_transform = transforms.Compose([ transforms.RandomResizedCrop(224), transforms.RandomHorizontalFlip(), # 随机水平翻转 transforms.ColorJitter(brightness=0.2, contrast=0.2, saturation=0.2, hue=0.1), # 随机颜色抖动 transforms.RandomRotation(degrees=15), # 随机旋转 transforms.ToTensor(), # This should come before Normalize transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), # This should be after ToTensor ]) train_dataset: ImageFolder = datasets.ImageFolder(root=train_data_dir, transform=data_transform) val_dataset = datasets.ImageFolder(root=val_data_dir, transform=data_transform) dataloaders = { 'train': torch.utils.data.DataLoader(train_dataset, batch_size=32, shuffle=True, num_workers=4), 'val': torch.utils.data.DataLoader(val_dataset, batch_size=32, shuffle=False, num_workers=4), } # ResNet-18 模型定义 model = models.swin_b(pretrained=True) num_ftrs = model.head.in_features # 获取最后一个线性层输入的特征数量 model.head = nn.Linear(num_ftrs, 2) # 创建一个新的线性层，输出特征维度为 2 # 损失函数和优化器 criterion = nn.CrossEntropyLoss() optimizer = optim.SGD(model.parameters(), lr=0.0001) # 将模型和数据移动到GPU上 num_epochs = 100 device = torch.device("cuda" if torch.cuda.is_available() else "cpu") model = model.to(device) train_losses = [] val_losses = [] train_accuracies = [] val_accuracies = [] best_val_labels = [] best_val_preds = [] for epoch in range(num_epochs): for phase in ['train', 'val']: if phase == 'train': model.train() else: model.eval() running_loss = 0.0 running_corrects = 0 all_labels = [] all_preds = [] for inputs, labels in dataloaders[phase]: inputs, labels = inputs.to(device), labels.to(device) optimizer.zero_grad() with torch.set_grad_enabled(phase == 'train'): outputs = model(inputs) loss = criterion(outputs, labels) if phase == 'train': loss.backward() optimizer.step() running_loss += loss.item() * inputs.size(0) _, preds = torch.max(outputs, 1) running_corrects += torch.sum(preds == labels.data) if phase == 'val': all_labels.extend(labels.cpu().numpy()) all_preds.extend(preds.cpu().numpy()) epoch_loss = running_loss / len(dataloaders[phase].dataset) epoch_acc = running_corrects.double() / len(dataloaders[phase].dataset) print(f'Epoch {epoch}/{num_epochs} | {phase} | Loss: {epoch_loss:.4f} | Acc: {epoch_acc:.4f}') if phase == 'train': train_losses.append(epoch_loss) train_accuracies.append(epoch_acc) else: val_losses.append(epoch_loss) val_accuracies.append(epoch_acc) if epoch_acc > best_accuracy: best_accuracy = epoch_acc torch.save(model.state_dict(), 'best_model.pth') best_val_labels = all_labels best_val_preds = all_preds # 加载最佳模型参数 model.load_state_dict(torch.load('best_model.pth')) # 可视化部分... # 绘制 Loss 曲线图 plt.figure(figsize=(10, 5)) plt.plot(train_losses, label='Training Loss') plt.plot(val_losses, label='Validation Loss') plt.xlabel('Epochs') plt.ylabel('Loss') plt.title('Training and Validation Loss') plt.legend() plt.show() # 绘制 Accuracy 曲线图 plt.figure(figsize=(10, 5)) plt.plot(train_accuracies, label='Training Accuracy') plt.plot(val_accuracies, label='Validation Accuracy') plt.xlabel('Epochs') plt.ylabel('Accuracy') plt.title('Training and Validation Accuracy') plt.legend() plt.show() # 使用 best_val_labels 和 best_val_preds 来计算混淆矩阵 conf_matrix = confusion_matrix(best_val_labels, best_val_preds) print("Confusion Matrix:") print(conf_matrix) # 绘制混淆矩阵图 class_names = sorted(train_dataset.classes) disp = ConfusionMatrixDisplay(confusion_matrix=conf_matrix, display_labels=class_names) disp.plot(cmap='Blues', values_format='d') plt.title('Confusion Matrix') plt.show() # 计算 ROC 曲线和 AUC fpr, tpr, _ = roc_curve(best_val_labels, best_val_preds) roc_auc = auc(fpr, tpr) # 首先计算混淆矩阵 conf_matrix = confusion_matrix(best_val_labels, best_val_preds) # 对于二分类，混淆矩阵布局如下： # TN FP # FN TP TN, FP, FN, TP = conf_matrix.ravel() # 计算特异度和灵敏度 Specificity = TN / (TN + FP) Sensitivity = TP / (TP + FN) print(f'Specificity: {Specificity:.4f}') print(f'Sensitivity: {Sensitivity:.4f}') # 绘制 ROC 曲线 plt.figure(figsize=(8, 8)) plt.plot(fpr, tpr, color='darkorange', lw=2, label=f'AUC = {roc_auc:.2f}') plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--') plt.xlim([0.0, 1.0]) plt.ylim([0.0, 1.05]) plt.xlabel('False Positive Rate') plt.ylabel('True Positive Rate') plt.title('Receiver Operating Characteristic') plt.legend(loc="lower right") plt.show() # 输出最佳准确度 print(f'Best Validation Accuracy: {best_accuracy:.4f}')

guialfaro/gemma-2-9b-it-pytorch-awq

guialfaro

2024-06-28T01:53:34Z

0

null

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

null

2024-06-28T01:53:34Z

--- license: gemma ---

LuuNgoc2k2/ViNER-MDeberta

LuuNgoc2k2

2024-06-28T01:59:23Z

0

null

[ "pytorch", "region:us" ]

null

2024-06-28T01:57:58Z

Entry not found

chrisliu298/tofu_forget01_classifier

chrisliu298

2024-06-28T02:10:32Z

0

transformers

[ "transformers", "safetensors", "roberta", "text-classification", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-06-28T02:08:52Z

--- library_name: transformers tags: [] --- A `roberta-base` classifier that classifies if a prompt belongs to the `forget01` split of the [TOFU dataset](https://huggingface.co/datasets/locuslab/TOFU).

AdamKasumovic/llama3-8b-instruct-bactrian-x-af-100-percent-med-high-perplexity

AdamKasumovic

2024-06-28T02:09:43Z

0

transformers

[ "transformers", "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

2024-06-28T02:09:43Z

--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - **Developed by:** AdamKasumovic - **License:** apache-2.0 - **Finetuned from model :** unsloth/llama-3-8b-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)

abdiharyadi/indoamrbart-mbart-triple-ft-parser-no-nst-128-eps

abdiharyadi

2024-06-28T02:12:52Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-28T02:10:40Z

Entry not found

ashprengel/mistral_b_finance_finetuned_test

ashprengel

2024-06-28T02:10:55Z

0

transformers

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

null

2024-06-28T02:10:44Z

--- 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]

Anujgr8/wav2vec2-base-Gujraati-large-4.5

Anujgr8

2024-06-28T02:52:51Z

0

transformers

[ "transformers", "tensorboard", "safetensors", "wav2vec2", "automatic-speech-recognition", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2024-06-28T02:10:45Z

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

KYUNGHYUN9/itos_v0.003_1.3b-1000step_longdata

KYUNGHYUN9

2024-06-28T02:12:43Z

0

transformers

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

null

2024-06-28T02:12:39Z

--- 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]

Jaqueline26/Imdimaq

Jaqueline26

2024-06-28T02:13:21Z

0

null

[ "region:us" ]

null

2024-06-28T02:13:21Z

Entry not found

NamHunter99/namzephyr-7b-lora-4bit

NamHunter99

2024-06-28T02:18:51Z

0

null

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

null

2024-06-28T02:16:18Z

--- license: apache-2.0 ---

patie/bert-finetuned-squad

patie

2024-06-28T02:17:48Z

0

null

[ "region:us" ]

null

2024-06-28T02:17:48Z

Entry not found

thesven/Aether-Code-Mistral-7B-0.3-v1-4bit-adapter

thesven

2024-06-28T02:19:07Z

0

transformers

[ "transformers", "safetensors", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:unsloth/mistral-7b-v0.3-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

2024-06-28T02:18:14Z

--- base_model: unsloth/mistral-7b-v0.3-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - **Developed by:** thesven - **License:** apache-2.0 - **Finetuned from model :** unsloth/mistral-7b-v0.3-bnb-4bit This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

chaewoners/HanJisungOfStrayKids

chaewoners

2024-06-28T02:22:19Z

0

null

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

null

2024-06-28T02:21:56Z

--- license: unknown ---

oranchatbot/Oran

oranchatbot

2024-06-28T02:24:03Z

0

null

[ "region:us" ]

null

2024-06-28T02:24:03Z

Entry not found

Arodrigo/temp005

Arodrigo

2024-06-28T02:24:36Z

0

transformers

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

null

2024-06-28T02:24:30Z

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

OceanandWild/Ocean

OceanandWild

2024-06-28T02:27:52Z

0

null

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

null

2024-06-28T02:27:52Z

--- license: mit ---

Elagra/UPN

Elagra

2024-06-28T02:29:36Z

0

null

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

null

2024-06-28T02:29:36Z

--- license: other license_name: python license_link: LICENSE ---

SD2000/example-model

SD2000

2024-06-28T16:39:36Z

0

null

[ "region:us" ]

null

2024-06-28T02:31:04Z

# Example Model This is a model card README --- license: mit ---

Elagra/alex_upn

Elagra

2024-06-28T02:31:40Z

0

null

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

null

2024-06-28T02:31:40Z

--- license: apache-2.0 ---

fabriziofalcon26/docs

fabriziofalcon26

2024-06-28T03:03:11Z

0

null

[ "region:us" ]

null

2024-06-28T02:32:16Z

Entry not found

Arodrigo/temp007

Arodrigo

2024-06-28T02:37:14Z

0

transformers

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

null

2024-06-28T02:37:09Z

--- 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]

Skeptical-Chafferer/code-llama-7b-text-to-sql

Skeptical-Chafferer

2024-06-28T02:53:59Z

0

null

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

null

2024-06-28T02:42:09Z

Entry not found

Bart0522/test0628

Bart0522

2024-06-28T02:44:12Z

0

null

[ "license:bsl-1.0", "region:us" ]

null

2024-06-28T02:44:12Z

--- license: bsl-1.0 ---

nam194/qwen2-7b-qlora-testcasegen-unsloth

nam194

2024-06-28T02:44:38Z

0

null

[ "region:us" ]

null

2024-06-28T02:44:38Z

Entry not found

tino123j/tcp2023

tino123j

2024-06-28T02:45:49Z

0

null

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

null

2024-06-28T02:45:49Z

--- license: apache-2.0 ---

setoutlas/tcp2023

setoutlas

2024-06-28T02:46:00Z

0

null

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

null

2024-06-28T02:46:00Z

--- license: apache-2.0 ---

guramiwei/tcp2023

guramiwei

2024-06-28T02:46:13Z

0

null

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

null

2024-06-28T02:46:13Z

--- license: apache-2.0 ---

Roxas22/tcp2023

Roxas22

2024-06-28T02:46:54Z

0

null

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

null

2024-06-28T02:46:54Z

--- license: apache-2.0 ---

GloryKuo/tcp2023

GloryKuo

2024-06-28T02:47:13Z

0

null

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

null

2024-06-28T02:47:13Z

--- license: apache-2.0 ---

HanYeh/tcp2023

HanYeh

2024-06-28T02:47:39Z

0

null

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

null

2024-06-28T02:47:39Z

--- license: apache-2.0 ---

AdamKasumovic/llama3-8b-instruct-bactrian-x-en-100-percent-low-perplexity

AdamKasumovic

2024-06-28T02:47:42Z

0

transformers

[ "transformers", "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

2024-06-28T02:47:41Z

--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - **Developed by:** AdamKasumovic - **License:** apache-2.0 - **Finetuned from model :** unsloth/llama-3-8b-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)

wu561092/tcp2023

wu561092

2024-06-28T02:48:03Z

0

null

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

null

2024-06-28T02:48:03Z

--- license: apache-2.0 ---

RIickMH/tcp2023

RIickMH

2024-06-28T02:48:21Z

0

null

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

null

2024-06-28T02:48:21Z

--- license: apache-2.0 ---

Dormir1010/tcp2023

Dormir1010

2024-06-28T02:48:22Z

0

null

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

null

2024-06-28T02:48:22Z

--- license: apache-2.0 ---

guosheng321/tcp2023

guosheng321

2024-06-28T02:48:43Z

0

null

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

null

2024-06-28T02:48:43Z

--- license: apache-2.0 ---

ZChieh/tcp2023

ZChieh

2024-06-28T02:48:45Z

0

null

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

null

2024-06-28T02:48:45Z

--- license: apache-2.0 ---

Dormir1010/uuu_fine_tune_gpt2

Dormir1010

2024-06-28T02:48:49Z

0

null

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

null

2024-06-28T02:48:49Z

--- license: apache-2.0 ---