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
AkumaLucif3r/GPT2-Chizuru	AkumaLucif3r	2024-06-27T20:09:11Z	0	null	[ "region:us" ]	null	2024-06-27T20:09:11Z	Entry not found
habulaj/7258553293	habulaj	2024-06-27T20:09:53Z	0	null	[ "region:us" ]	null	2024-06-27T20:09:50Z	Entry not found
imagepipeline/SEXUAL	imagepipeline	2024-06-27T20:12:27Z	0	null	[ "imagepipeline", "imagepipeline.io", "text-to-image", "ultra-realistic", "license:creativeml-openrail-m", "region:us" ]	text-to-image	2024-06-27T20:12:25Z	--- license: creativeml-openrail-m tags: - imagepipeline - imagepipeline.io - text-to-image - ultra-realistic pinned: false pipeline_tag: text-to-image --- ## SEXUAL <img src="https://via.placeholder.com/468x300?text=App+Screenshot+Here" alt="Generated on Image Pipeline" style="border-radius: 10px;"> This lora model is uploaded on [imagepipeline.io](https://imagepipeline.io/) Model details - SEXUAL [![Try this model](https://img.shields.io/badge/try_this_model-image_pipeline-BD9319)](https://imagepipeline.io/models/SEXUAL?id=4d3ab6d7-eef9-4603-9062-7b76b5b08d78/) ## How to try this model ? You can try using it locally or send an API call to test the output quality. Get your `API_KEY` from [imagepipeline.io](https://imagepipeline.io/). No payment required. Coding in `php` `javascript` `node` etc ? Checkout our documentation [![documentation](https://img.shields.io/badge/documentation-image_pipeline-blue)](https://docs.imagepipeline.io/docs/introduction) ```python import requests import json url = "https://imagepipeline.io/sd/text2image/v1/run" payload = json.dumps({ "model_id": "sd1.5", "prompt": "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K", "negative_prompt": "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime", "width": "512", "height": "512", "samples": "1", "num_inference_steps": "30", "safety_checker": false, "guidance_scale": 7.5, "multi_lingual": "no", "embeddings": "", "lora_models": "4d3ab6d7-eef9-4603-9062-7b76b5b08d78", "lora_weights": "0.5" }) headers = { 'Content-Type': 'application/json', 'API-Key': 'your_api_key' } response = requests.request("POST", url, headers=headers, data=payload) print(response.text) } ``` Get more ready to use `MODELS` like this for `SD 1.5` and `SDXL` : [![All models](https://img.shields.io/badge/Get%20All%20Models-image_pipeline-BD9319)](https://imagepipeline.io/models) ### API Reference #### Generate Image ```http https://api.imagepipeline.io/sd/text2image/v1 ``` \| Headers \| Type \| Description \| \|:----------------------\| :------- \|:-------------------------------------------------------------------------------------------------------------------\| \| `API-Key` \| `str` \| Get your `API_KEY` from [imagepipeline.io](https://imagepipeline.io/) \| \| `Content-Type` \| `str` \| application/json - content type of the request body \| \| Parameter \| Type \| Description \| \| :-------- \| :------- \| :------------------------- \| \| `model_id` \| `str` \| Your base model, find available lists in [models page](https://imagepipeline.io/models) or upload your own\| \| `prompt` \| `str` \| Text Prompt. Check our [Prompt Guide](https://docs.imagepipeline.io/docs/SD-1.5/docs/extras/prompt-guide) for tips \| \| `num_inference_steps` \| `int [1-50]` \| Noise is removed with each step, resulting in a higher-quality image over time. Ideal value 30-50 (without LCM) \| \| `guidance_scale` \| `float [1-20]` \| Higher guidance scale prioritizes text prompt relevance but sacrifices image quality. Ideal value 7.5-12.5 \| \| `lora_models` \| `str, array` \| Pass the model_id(s) of LoRA models that can be found in models page \| \| `lora_weights` \| `str, array` \| Strength of the LoRA effect \| --- license: creativeml-openrail-m tags: - imagepipeline - imagepipeline.io - text-to-image - ultra-realistic pinned: false pipeline_tag: text-to-image --- ### Feedback If you have any feedback, please reach out to us at [email protected] #### 🔗 Visit Website [![portfolio](https://img.shields.io/badge/image_pipeline-BD9319?style=for-the-badge&logo=gocd&logoColor=white)](https://imagepipeline.io/) If you are the original author of this model, please [click here](https://airtable.com/apprTaRnJbDJ8ufOx/shr4g7o9B6fWfOlUR) to add credits
MtsRibeiroArq/facade	MtsRibeiroArq	2024-06-27T20:14:19Z	0	null	[ "region:us" ]	null	2024-06-27T20:14:19Z	Entry not found
xkronosx/train_posterior_mnist_cls-batched-rtb-bs_7	xkronosx	2024-06-27T20:20:04Z	0	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:xkronosx/ddpm-mnist-32", "region:us" ]	null	2024-06-27T20:19:39Z	--- library_name: peft base_model: xkronosx/ddpm-mnist-32 --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.10.0
fleh/stage_model	fleh	2024-06-27T20:19:58Z	0	null	[ "region:us" ]	null	2024-06-27T20:19:58Z	Entry not found
Rupesh2/Llama-3-uncensored-dare	Rupesh2	2024-06-27T20:20:40Z	0	null	[ "region:us" ]	null	2024-06-27T20:20:40Z	Entry not found
Mananb141/Gaip	Mananb141	2024-06-27T20:26:22Z	0	null	[ "license:mit", "region:us" ]	null	2024-06-27T20:23:02Z	--- title: Car Parts Damage Detection emoji: 😻 colorFrom: gray colorTo: green sdk: gradio sdk_version: 3.11.0 app_file: app.py pinned: false license: mit --- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
gaelafoxuk/LoraPonyXL	gaelafoxuk	2024-06-28T19:54:03Z	0	null	[ "region:us" ]	null	2024-06-27T20:26:31Z	Entry not found
ekaterina-blatova-jb/model_lr1e-4_old_scheduler_with_t_max_275_v2	ekaterina-blatova-jb	2024-06-27T20:29:23Z	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text-generation	2024-06-27T20:27:50Z	--- {} --- ## Evaluation results Validation loss on the whole input: 0.8595233634114265 Validation loss on completion: 0.9250378025462851
amirmm03/Movie_Genre_Classifier	amirmm03	2024-06-27T20:28:36Z	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-06-27T20:28:14Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
csikasote/huggingface	csikasote	2024-06-27T20:32:58Z	0	null	[ "region:us" ]	null	2024-06-27T20:32:58Z	Entry not found
habulaj/7325453667	habulaj	2024-06-27T20:34:54Z	0	null	[ "region:us" ]	null	2024-06-27T20:34:43Z	Entry not found
Maxivi/SDXLLightning	Maxivi	2024-06-28T19:01:48Z	0	null	[ "region:us" ]	null	2024-06-27T20:42:27Z	Entry not found
dOXINHO/srdoxinhoa	dOXINHO	2024-06-27T20:43:22Z	0	null	[ "region:us" ]	null	2024-06-27T20:43:22Z	Entry not found
AliAvd/Movie_Genre_Classifier	AliAvd	2024-06-27T20:46:36Z	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T20:46:09Z	--- 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]
Solux77/Zadani	Solux77	2024-06-27T20:46:25Z	0	null	[ "doi:10.57967/hf/2634", "license:cc-by-nc-2.0", "region:us" ]	null	2024-06-27T20:46:25Z	--- license: cc-by-nc-2.0 ---
Suchae/test-finetuned	Suchae	2024-06-27T20:47:39Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T20:46:59Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
yuan-yang/Tiger-PJ-8B	yuan-yang	2024-06-27T22:52:01Z	0	null	[ "safetensors", "arxiv:2406.13764", "license:apache-2.0", "region:us" ]	null	2024-06-27T20:48:13Z	--- license: apache-2.0 --- # Tiger Model Card ## Model details Tactic-guided reasoner (Tiger) is a language model that solves reasoning in the wild task proposed in paper [Can LLMs Reason in the Wild with Programs](https://arxiv.org/abs/2406.13764). It is trained by fine-tuning the LLaMA3-8B model on the [ReWild](https://huggingface.co/datasets/yuan-yang/ReWild) dataset. Model type: This repo contains the LoRA delta weights for `Tiger-PJ-8B` We also provide the delta weights of other versions: - [Tiger-Routing-8B](https://huggingface.co/yuan-yang/Tiger-Routing-8B/) - [Tiger-PJ-8B](https://huggingface.co/yuan-yang/Tiger-PJ-8B) - [Tiger-IPJ-8B](https://huggingface.co/yuan-yang/Tiger-IPJ-8B) License: Apache License 2.0 ## Using the model Check out how to use the model on our project page: https://github.com/gblackout/Reason-in-the-Wild/ Primary intended uses: Tiger is intended to be used for research. ## Citation ``` @article{yang2024can, title={Can LLMs Reason in the Wild with Programs?}, author={Yang, Yuan and Xiong, Siheng and Payani, Ali and Shareghi, Ehsan and Fekri, Faramarz}, journal={arXiv preprint arXiv:2406.13764}, year={2024} } ```
yuan-yang/Tiger-IPJ-8B	yuan-yang	2024-06-27T22:52:56Z	0	null	[ "safetensors", "arxiv:2406.13764", "license:apache-2.0", "region:us" ]	null	2024-06-27T20:48:34Z	--- license: apache-2.0 --- # Tiger Model Card ## Model details Tactic-guided reasoner (Tiger) is a language model that solves reasoning in the wild task proposed in paper [Can LLMs Reason in the Wild with Programs](https://arxiv.org/abs/2406.13764). It is trained by fine-tuning the LLaMA3-8B model on the [ReWild](https://huggingface.co/datasets/yuan-yang/ReWild) dataset. Model type: This repo contains the LoRA delta weights for `Tiger-IPJ-8B` We also provide the delta weights of other versions: - [Tiger-Routing-8B](https://huggingface.co/yuan-yang/Tiger-Routing-8B/) - [Tiger-PJ-8B](https://huggingface.co/yuan-yang/Tiger-PJ-8B) - [Tiger-IPJ-8B](https://huggingface.co/yuan-yang/Tiger-IPJ-8B) License: Apache License 2.0 ## Using the model Check out how to use the model on our project page: https://github.com/gblackout/Reason-in-the-Wild/ Primary intended uses: Tiger is intended to be used for research. ## Citation ``` @article{yang2024can, title={Can LLMs Reason in the Wild with Programs?}, author={Yang, Yuan and Xiong, Siheng and Payani, Ali and Shareghi, Ehsan and Fekri, Faramarz}, journal={arXiv preprint arXiv:2406.13764}, year={2024} } ```
yuan-yang/Tiger-Routing-8B	yuan-yang	2024-06-27T22:50:33Z	0	null	[ "safetensors", "arxiv:2406.13764", "license:apache-2.0", "region:us" ]	null	2024-06-27T20:49:06Z	--- license: apache-2.0 --- # Tiger Model Card ## Model details Tactic-guided reasoner (Tiger) is a language model that solves reasoning in the wild task proposed in paper [Can LLMs Reason in the Wild with Programs](https://arxiv.org/abs/2406.13764). It is trained by fine-tuning the LLaMA3-8B model on the [ReWild](https://huggingface.co/datasets/yuan-yang/ReWild) dataset. Model type: This repo contains the LoRA delta weights for `Tiger-Routing-8B` We also provide the delta weights of other versions: - [Tiger-Routing-8B](https://huggingface.co/yuan-yang/Tiger-Routing-8B/) - [Tiger-PJ-8B](https://huggingface.co/yuan-yang/Tiger-PJ-8B) - [Tiger-IPJ-8B](https://huggingface.co/yuan-yang/Tiger-IPJ-8B) License: Apache License 2.0 ## Using the model Check out how to use the model on our project page: https://github.com/gblackout/Reason-in-the-Wild/ Primary intended uses: Tiger is intended to be used for research. ## Citation ``` @article{yang2024can, title={Can LLMs Reason in the Wild with Programs?}, author={Yang, Yuan and Xiong, Siheng and Payani, Ali and Shareghi, Ehsan and Fekri, Faramarz}, journal={arXiv preprint arXiv:2406.13764}, year={2024} } ```
Litzy619/MIS0626T6F200200	Litzy619	2024-06-27T20:49:13Z	0	null	[ "region:us" ]	null	2024-06-27T20:49:13Z	Entry not found
sulph/quasarcake	sulph	2024-06-28T11:05:33Z	1	null	[ "license:openrail", "region:us" ]	null	2024-06-27T20:54:58Z	--- license: openrail ---
louistichelman/controlnet_streetview_segmentation_city2	louistichelman	2024-06-27T20:56:29Z	0	null	[ "region:us" ]	null	2024-06-27T20:56:29Z	Entry not found
sparsh35/deepseekmathslastft	sparsh35	2024-06-27T20:56:33Z	0	null	[ "region:us" ]	null	2024-06-27T20:56:33Z	Entry not found
Muradn/Han_Kanal-Oguzhan_Bostan	Muradn	2024-06-27T21:06:27Z	0	null	[ "license:openrail++", "region:us" ]	null	2024-06-27T21:05:15Z	--- license: openrail++ ---
valerielucro/mistral_gsm8k_preference_dataset_v2.1	valerielucro	2024-06-27T21:08:59Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T21:08:22Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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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]
howarudo/paligemma-3b-pt-224-vqa-continue-ft-5	howarudo	2024-06-27T21:10:56Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T21:10:37Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
arhanovich/ds_3000gb	arhanovich	2024-06-28T23:28:06Z	0	null	[ "region:us" ]	null	2024-06-27T21:12:59Z	Entry not found
habulaj/5423391019	habulaj	2024-06-27T21:15:38Z	0	null	[ "region:us" ]	null	2024-06-27T21:15:28Z	Entry not found
habulaj/182895157431	habulaj	2024-06-27T21:15:45Z	0	null	[ "region:us" ]	null	2024-06-27T21:15:36Z	Entry not found
ycfNTU/B_hope_lora_llama7b	ycfNTU	2024-06-27T21:18:19Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T21:18:10Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
habulaj/36793907	habulaj	2024-06-27T21:21:21Z	0	null	[ "region:us" ]	null	2024-06-27T21:21:19Z	Entry not found
Darshandev/Future-Insight-Predicto	Darshandev	2024-06-27T21:24:33Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-27T21:23:31Z	--- license: apache-2.0 --- ## Future Insight Predictor This Streamlit application helps you predict future values based on historical data in a CSV file. It offers various machine learning algorithms to choose from and provides informative visualizations to assess model performance. ### Getting Started 1. Prerequisites: - Python 3.x - Streamlit: `pip install streamlit` - Pandas: `pip install pandas` - scikit-learn: `pip install scikit-learn` - matplotlib: `pip install matplotlib` - seaborn: `pip install seaborn` 2. Run the app: - Save the code as `app.py`. - Open a terminal, navigate to the directory containing the file, and run: ```bash streamlit run app.py ``` ### How it Works 1. Upload a CSV file containing your historical data. 2. The app will display a preview of the data. 3. Preprocessing is applied to format the data for modeling. 4. Select the features (independent variables) and target variable (dependent variable) for prediction. 5. Choose a prediction task based on your data domain (e.g., Stock Sale, Real Estate Prices). 6. Select a machine learning algorithm for prediction. 7. Click "Train and Evaluate" to train the model and view the results. ### Output - The predicted value for the next month. - Model accuracy score and cross-validation scores for evaluation. - Visualization comparing actual vs predicted values, highlighting overestimations and underestimations. ### Note This is a basic implementation and can be further enhanced with additional features and functionalities based on your specific needs. ### Contributing Feel free to fork the repository and submit pull requests with improvements or additional features!
sahielbose/plant-detection-model	sahielbose	2024-06-27T21:24:08Z	0	null	[ "region:us" ]	null	2024-06-27T21:24:08Z	Entry not found
whizzzzkid/whizzzzkid_235_4	whizzzzkid	2024-06-27T21:25:58Z	0	transformers	[ "transformers", "safetensors", "stablelm", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-06-27T21:24:14Z	Entry not found
pursuitofds/finetuned_qa_llama3_8b_qlora_model	pursuitofds	2024-06-28T14:47:09Z	0	Llama-3-8B-peft-QA-QLoRa	[ "Llama-3-8B-peft-QA-QLoRa", "safetensors", "base_model:pursuitofds/finetuned_qa_llama3_8b_qlora_model", "region:us" ]	null	2024-06-27T21:24:32Z	--- library_name: Llama-3-8B-peft-QA-QLoRa base_model: pursuitofds/finetuned_qa_llama3_8b_qlora_model --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> The model is finetuned on the SQUAD2 dataset using QLora. - Model type: [More Information Needed] - Language(s) (NLP): English - Finetuned from model [optional]: Llama3-8B ## Uses ```python from transformers import AutoModelForQuestionAnswering, AutoTokenizer model = AutoModelForQuestionAnswering.from_pretrained("pursuitofds/finetuned_qa_llama3_8b_qlora_model") tokenizer = AutoTokenizer.from_pretrained("pursuitofds/finetuned_qa_llama3_8b_qlora_model") inputs = tokenizer("What is the capital of France?", return_tensors="pt") outputs = model(**inputs) answer_start = outputs.start_logits.argmax() answer_end = outputs.end_logits.argmax() + 1 answer = tokenizer.convert_tokens_to_string(tokenizer.convert_ids_to_tokens(inputs.input_ids[0][answer_start:answer_end])) print(answer) # Should print "Paris"
whizzzzkid/whizzzzkid_233_1	whizzzzkid	2024-06-27T21:26:49Z	0	transformers	[ "transformers", "safetensors", "stablelm", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-06-27T21:25:03Z	Entry not found
jessylin/vllama3	jessylin	2024-06-28T01:01:41Z	0	null	[ "region:us" ]	null	2024-06-27T21:25:26Z	Entry not found
mabrouk/first-model	mabrouk	2024-06-27T21:27:47Z	0	null	[ "region:us" ]	null	2024-06-27T21:27:47Z	Entry not found
NRbones/Hancock	NRbones	2024-06-27T21:38:08Z	0	null	[ "region:us" ]	null	2024-06-27T21:27:51Z	Entry not found
habulaj/542318517965	habulaj	2024-06-27T21:29:27Z	0	null	[ "region:us" ]	null	2024-06-27T21:29:24Z	Entry not found
shiromiya/fairseq-hubert-portuguese	shiromiya	2024-06-29T02:15:18Z	1	null	[ "region:us" ]	null	2024-06-27T21:29:37Z	Entry not found
habulaj/328166294230	habulaj	2024-06-27T21:30:29Z	0	null	[ "region:us" ]	null	2024-06-27T21:30:26Z	Entry not found
whizzzzkid/whizzzzkid_236_5	whizzzzkid	2024-06-27T21:32:49Z	0	transformers	[ "transformers", "safetensors", "stablelm", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-06-27T21:31:04Z	Entry not found
Arodrigo/temp001	Arodrigo	2024-06-27T21:31:35Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T21:31:27Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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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]
Pra-tham/whisper-peft-full-labelled	Pra-tham	2024-06-28T06:54:04Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T21:31:57Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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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]
JEFFERSONMUSIC/BRUNEIHWT1996	JEFFERSONMUSIC	2024-06-27T21:34:00Z	0	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-27T21:32:52Z	--- license: apache-2.0 ---
huggingfacepremium/autotrain-t5jjv-fxr8g	huggingfacepremium	2024-06-27T23:16:58Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "autotrain", "text-generation-inference", "text-generation", "peft", "conversational", "dataset:huggingfacepremium/kober1", "base_model:microsoft/Phi-3-mini-4k-instruct", "license:other", "endpoints_compatible", "region:us" ]	text-generation	2024-06-27T21:33:44Z	--- tags: - autotrain - text-generation-inference - text-generation - peft library_name: transformers base_model: microsoft/Phi-3-mini-4k-instruct widget: - messages: - role: user content: What is your favorite condiment? license: other datasets: - huggingfacepremium/kober1 --- # Model Trained Using AutoTrain This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain). # Usage ```python from transformers import AutoModelForCausalLM, AutoTokenizer model_path = "PATH_TO_THIS_REPO" tokenizer = AutoTokenizer.from_pretrained(model_path) model = AutoModelForCausalLM.from_pretrained( model_path, device_map="auto", torch_dtype='auto' ).eval() # Prompt content: "hi" messages = [ {"role": "user", "content": "hi"} ] input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt') output_ids = model.generate(input_ids.to('cuda')) response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True) # Model response: "Hello! How can I assist you today?" print(response) ```
thibautweber/fraud_detection_updated	thibautweber	2024-06-27T21:34:40Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:unsloth/mistral-7b-instruct-v0.2-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T21:34:26Z	--- base_model: unsloth/mistral-7b-instruct-v0.2-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - Developed by: thibautweber - License: apache-2.0 - Finetuned from model : unsloth/mistral-7b-instruct-v0.2-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)
habulaj/327396293447	habulaj	2024-06-27T21:36:53Z	0	null	[ "region:us" ]	null	2024-06-27T21:36:50Z	Entry not found
habulaj/8001357917	habulaj	2024-06-27T21:42:04Z	0	null	[ "region:us" ]	null	2024-06-27T21:41:57Z	Entry not found
habulaj/542342517989	habulaj	2024-06-27T21:44:15Z	0	null	[ "region:us" ]	null	2024-06-27T21:44:12Z	Entry not found
hammadsaleem/sdqn-SpaceInvadersNoFrameskip-v4	hammadsaleem	2024-06-27T21:51:49Z	0	null	[ "region:us" ]	null	2024-06-27T21:51:49Z	Entry not found
Coolwowsocoolwow/Waluigi	Coolwowsocoolwow	2024-06-27T21:55:09Z	0	null	[ "license:openrail", "region:us" ]	null	2024-06-27T21:52:21Z	--- license: openrail ---
Tonygab/Male	Tonygab	2024-06-27T21:54:26Z	0	null	[ "license:openrail", "region:us" ]	null	2024-06-27T21:53:20Z	--- license: openrail ---
habulaj/1189616542	habulaj	2024-06-27T21:54:34Z	0	null	[ "region:us" ]	null	2024-06-27T21:54:27Z	Entry not found
habulaj/318093284580	habulaj	2024-06-27T21:56:37Z	0	null	[ "region:us" ]	null	2024-06-27T21:56:35Z	Entry not found
Hnhasni/Voice	Hnhasni	2024-06-27T21:59:34Z	0	null	[ "region:us" ]	null	2024-06-27T21:59:34Z	Entry not found
X0x0G/Lisa_Mimi_Capstone	X0x0G	2024-06-27T22:00:09Z	0	null	[ "region:us" ]	null	2024-06-27T22:00:09Z	Entry not found
tokare163/Bdjsjzjzjxjx	tokare163	2024-06-27T22:01:39Z	0	null	[ "region:us" ]	null	2024-06-27T22:01:39Z	Entry not found
ayse0/garbage_classification_model	ayse0	2024-06-27T22:03:55Z	0	null	[ "license:mit", "region:us" ]	null	2024-06-27T22:03:55Z	--- license: mit ---
asemane/Movie_Genre_Classifier	asemane	2024-06-27T22:24:16Z	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T22:04:25Z	--- 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]
AdamKasumovic/phi3-mini-4k-instruct-bactrian-x-en-100-percent-med-perplexity-mmlu_ck	AdamKasumovic	2024-06-27T22:08:44Z	0	transformers	[ "transformers", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:unsloth/Phi-3-mini-4k-instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T22:08:44Z	--- base_model: unsloth/Phi-3-mini-4k-instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - Developed by: AdamKasumovic - License: apache-2.0 - Finetuned from model : unsloth/Phi-3-mini-4k-instruct-bnb-4bit This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
habulaj/61099187815	habulaj	2024-06-27T22:11:26Z	0	null	[ "region:us" ]	null	2024-06-27T22:11:24Z	Entry not found
habulaj/11033485185	habulaj	2024-06-27T22:11:31Z	0	null	[ "region:us" ]	null	2024-06-27T22:11:28Z	Entry not found
tctrautman/20240627-kibbe-prod-with-no-celeb-data	tctrautman	2024-06-27T22:12:55Z	0	null	[ "safetensors", "generated_from_trainer", "base_model:HuggingFaceM4/idefics2-8b", "license:apache-2.0", "region:us" ]	null	2024-06-27T22:12:51Z	--- license: apache-2.0 base_model: HuggingFaceM4/idefics2-8b tags: - generated_from_trainer model-index: - name: 20240627-kibbe-prod-with-no-celeb-data 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/8aq6w9lt) # 20240627-kibbe-prod-with-no-celeb-data 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: 0.0289 ## 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 \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.9221 \| 0.5005 \| 510 \| 0.0337 \| \| 0.5426 \| 1.0010 \| 1020 \| 0.0324 \| \| 0.6505 \| 1.5015 \| 1530 \| 0.0289 \| ### Framework versions - Transformers 4.43.0.dev0 - Pytorch 2.1.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1
sankar-a/llm_test	sankar-a	2024-06-27T22:14:45Z	0	null	[ "region:us" ]	null	2024-06-27T22:14:45Z	Entry not found
Heruss/FDA	Heruss	2024-06-27T22:17:37Z	0	null	[ "region:us" ]	null	2024-06-27T22:16:48Z	Entry not found
Heruss/LRSADAWNG	Heruss	2024-06-27T22:19:18Z	0	null	[ "region:us" ]	null	2024-06-27T22:18:34Z	Entry not found
howarudo/paligemma-3b-pt-224-vqa-continue-ft-6	howarudo	2024-06-27T22:19:26Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T22:19:05Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
ChenmieNLP/SELM-Llama-3-8B-Instruct-iter-1	ChenmieNLP	2024-06-27T22:19:10Z	0	null	[ "region:us" ]	null	2024-06-27T22:19:10Z	Entry not found
nglguarino/my-nlp-gemma-model2	nglguarino	2024-06-27T22:20:06Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "gemma", "trl", "en", "base_model:unsloth/gemma-2b-it-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T22:19:57Z	--- base_model: unsloth/gemma-2b-it-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - gemma - trl --- # Uploaded model - Developed by: nglguarino - License: apache-2.0 - Finetuned from model : unsloth/gemma-2b-it-bnb-4bit This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
AdamKasumovic/phi3-mini-4k-instruct-bactrian-x-en-100-percent-low-perplexity-mmlu_ck	AdamKasumovic	2024-06-27T22:22:18Z	0	transformers	[ "transformers", "safetensors", "mistral", "text-generation", "text-generation-inference", "unsloth", "trl", "conversational", "en", "base_model:unsloth/Phi-3-mini-4k-instruct-bnb-4bit", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-06-27T22:20:15Z	--- base_model: unsloth/Phi-3-mini-4k-instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - Developed by: AdamKasumovic - License: apache-2.0 - Finetuned from model : unsloth/Phi-3-mini-4k-instruct-bnb-4bit This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
habulaj/10219177243	habulaj	2024-06-27T22:21:11Z	0	null	[ "region:us" ]	null	2024-06-27T22:21:09Z	Entry not found
kevin009/babyllama07	kevin009	2024-06-28T00:49:24Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:TinyLlama/TinyLlama_v1.1_math_code", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T22:24:16Z	--- language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl base_model: TinyLlama/TinyLlama_v1.1_math_code --- # Uploaded model - Developed by: kevin009 - License: apache-2.0 - Finetuned from model : TinyLlama/TinyLlama_v1.1_math_code 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)
Arodrigo/temp002	Arodrigo	2024-06-27T22:25:48Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T22:25:41Z	--- 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]
Coolwowsocoolwow/WAHHH	Coolwowsocoolwow	2024-06-27T22:31:55Z	0	null	[ "license:openrail", "region:us" ]	null	2024-06-27T22:30:14Z	--- license: openrail ---
Litzy619/MIS0627T1F200200	Litzy619	2024-06-27T22:39:03Z	0	null	[ "region:us" ]	null	2024-06-27T22:39:03Z	Entry not found
Ramikan-BR/TiamaPY-LORA-v38	Ramikan-BR	2024-06-27T22:44:55Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:unsloth/tinyllama-chat-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T22:44:25Z	--- base_model: unsloth/tinyllama-chat-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: Ramikan-BR - License: apache-2.0 - Finetuned from model : unsloth/tinyllama-chat-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)
ness321/Indonesia-BERT-QA	ness321	2024-06-27T22:44:51Z	0	null	[ "license:other", "region:us" ]	null	2024-06-27T22:44:51Z	--- license: other license_name: vaness license_link: LICENSE ---
Enkeeper/Gemma_2B_TaskInstruct_Unsloth_LORA	Enkeeper	2024-06-27T22:45:32Z	0	null	[ "safetensors", "license:gemma", "region:us" ]	null	2024-06-27T22:45:19Z	--- license: gemma ---
mpa21/video1	mpa21	2024-06-27T22:51:39Z	0	null	[ "license:openrail", "region:us" ]	null	2024-06-27T22:48:38Z	--- license: openrail ---
abdiharyadi/indoamrbart-mbart-triple-ft-parser-no-nst	abdiharyadi	2024-06-27T22:54:26Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-27T22:52:38Z	Entry not found
baseten/HR-finetune	baseten	2024-06-27T22:55:21Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-27T22:54:59Z	Entry not found
mmbutera/moka	mmbutera	2024-06-27T22:56:33Z	0	null	[ "license:openrail", "region:us" ]	null	2024-06-27T22:55:43Z	--- license: openrail ---
estepadilla/sne_classifier	estepadilla	2024-06-28T16:16:42Z	0	null	[ "license:mit", "region:us" ]	null	2024-06-27T22:59:56Z	--- license: mit ---
wopi/conv	wopi	2024-07-02T03:47:58Z	0	null	[ "region:us" ]	null	2024-06-27T23:05:38Z	Entry not found
anonymous55/blip-celeba-1000-100	anonymous55	2024-06-27T23:07:00Z	0	transformers	[ "transformers", "safetensors", "blip", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2024-06-27T23:06:37Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Ghareeb-M/my-finetuned-banking77-distilbert	Ghareeb-M	2024-07-01T17:02:31Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-06-27T23:15:44Z	Entry not found
ycfNTU/B_fear_lora_llama7b	ycfNTU	2024-06-27T23:21:30Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T23:21:20Z	--- 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]
abdiharyadi/indoamrbart-mbart-triple-ft-parser-no-nst-32-eps	abdiharyadi	2024-06-27T23:25:18Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-27T23:23:33Z	Entry not found
habulaj/242516214136	habulaj	2024-06-27T23:24:29Z	0	null	[ "region:us" ]	null	2024-06-27T23:24:23Z	Entry not found
habulaj/55296800	habulaj	2024-06-27T23:25:00Z	0	null	[ "region:us" ]	null	2024-06-27T23:24:55Z	Entry not found
fifala/08-fifa-06-28-01	fifala	2024-06-27T23:28:10Z	0	transformers	[ "transformers", "safetensors", "stablelm", "text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-06-27T23:25:39Z	Entry not found
Belvannn/Tyrone	Belvannn	2024-06-27T23:27:21Z	0	null	[ "license:openrail", "region:us" ]	null	2024-06-27T23:26:23Z	--- license: openrail ---
habulaj/49835951	habulaj	2024-06-27T23:26:56Z	0	null	[ "region:us" ]	null	2024-06-27T23:26:49Z	Entry not found
howarudo/paligemma-3b-pt-224-vqa-continue-ft-7	howarudo	2024-06-27T23:27:50Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T23:27:31Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
habulaj/236303207665	habulaj	2024-06-27T23:28:10Z	0	null	[ "region:us" ]	null	2024-06-27T23:28:01Z	Entry not found
adamo1139/Yi-34B-200K-HESOYAM-TURTLE-2606-5bpw-exl2	adamo1139	2024-06-27T23:41:12Z	0	transformers	[ "transformers", "llama", "text-generation", "conversational", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us" ]	text-generation	2024-06-27T23:28:20Z	--- license: apache-2.0 ---

AkumaLucif3r/GPT2-Chizuru

AkumaLucif3r

2024-06-27T20:09:11Z

0

null

[ "region:us" ]

null

2024-06-27T20:09:11Z

Entry not found

habulaj/7258553293

habulaj

2024-06-27T20:09:53Z

0

null

[ "region:us" ]

null

2024-06-27T20:09:50Z

Entry not found

imagepipeline/SEXUAL

imagepipeline

2024-06-27T20:12:27Z

0

null

[ "imagepipeline", "imagepipeline.io", "text-to-image", "ultra-realistic", "license:creativeml-openrail-m", "region:us" ]

text-to-image

2024-06-27T20:12:25Z

--- license: creativeml-openrail-m tags: - imagepipeline - imagepipeline.io - text-to-image - ultra-realistic pinned: false pipeline_tag: text-to-image --- ## SEXUAL <img src="https://via.placeholder.com/468x300?text=App+Screenshot+Here" alt="Generated on Image Pipeline" style="border-radius: 10px;"> **This lora model is uploaded on [imagepipeline.io](https://imagepipeline.io/)** Model details - SEXUAL [![Try this model](https://img.shields.io/badge/try_this_model-image_pipeline-BD9319)](https://imagepipeline.io/models/SEXUAL?id=4d3ab6d7-eef9-4603-9062-7b76b5b08d78/) ## How to try this model ? You can try using it locally or send an API call to test the output quality. Get your `API_KEY` from [imagepipeline.io](https://imagepipeline.io/). No payment required. Coding in `php` `javascript` `node` etc ? Checkout our documentation [![documentation](https://img.shields.io/badge/documentation-image_pipeline-blue)](https://docs.imagepipeline.io/docs/introduction) ```python import requests import json url = "https://imagepipeline.io/sd/text2image/v1/run" payload = json.dumps({ "model_id": "sd1.5", "prompt": "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K", "negative_prompt": "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime", "width": "512", "height": "512", "samples": "1", "num_inference_steps": "30", "safety_checker": false, "guidance_scale": 7.5, "multi_lingual": "no", "embeddings": "", "lora_models": "4d3ab6d7-eef9-4603-9062-7b76b5b08d78", "lora_weights": "0.5" }) headers = { 'Content-Type': 'application/json', 'API-Key': 'your_api_key' } response = requests.request("POST", url, headers=headers, data=payload) print(response.text) } ``` Get more ready to use `MODELS` like this for `SD 1.5` and `SDXL` : [![All models](https://img.shields.io/badge/Get%20All%20Models-image_pipeline-BD9319)](https://imagepipeline.io/models) ### API Reference #### Generate Image ```http https://api.imagepipeline.io/sd/text2image/v1 ``` | Headers | Type | Description | |:----------------------| :------- |:-------------------------------------------------------------------------------------------------------------------| | `API-Key` | `str` | Get your `API_KEY` from [imagepipeline.io](https://imagepipeline.io/) | | `Content-Type` | `str` | application/json - content type of the request body | | Parameter | Type | Description | | :-------- | :------- | :------------------------- | | `model_id` | `str` | Your base model, find available lists in [models page](https://imagepipeline.io/models) or upload your own| | `prompt` | `str` | Text Prompt. Check our [Prompt Guide](https://docs.imagepipeline.io/docs/SD-1.5/docs/extras/prompt-guide) for tips | | `num_inference_steps` | `int [1-50]` | Noise is removed with each step, resulting in a higher-quality image over time. Ideal value 30-50 (without LCM) | | `guidance_scale` | `float [1-20]` | Higher guidance scale prioritizes text prompt relevance but sacrifices image quality. Ideal value 7.5-12.5 | | `lora_models` | `str, array` | Pass the model_id(s) of LoRA models that can be found in models page | | `lora_weights` | `str, array` | Strength of the LoRA effect | --- license: creativeml-openrail-m tags: - imagepipeline - imagepipeline.io - text-to-image - ultra-realistic pinned: false pipeline_tag: text-to-image --- ### Feedback If you have any feedback, please reach out to us at [email protected] #### 🔗 Visit Website [![portfolio](https://img.shields.io/badge/image_pipeline-BD9319?style=for-the-badge&logo=gocd&logoColor=white)](https://imagepipeline.io/) If you are the original author of this model, please [click here](https://airtable.com/apprTaRnJbDJ8ufOx/shr4g7o9B6fWfOlUR) to add credits

MtsRibeiroArq/facade

MtsRibeiroArq

2024-06-27T20:14:19Z

0

null

[ "region:us" ]

null

2024-06-27T20:14:19Z

Entry not found

xkronosx/train_posterior_mnist_cls-batched-rtb-bs_7

xkronosx

2024-06-27T20:20:04Z

0

peft

[ "peft", "safetensors", "arxiv:1910.09700", "base_model:xkronosx/ddpm-mnist-32", "region:us" ]

null

2024-06-27T20:19:39Z

--- library_name: peft base_model: xkronosx/ddpm-mnist-32 --- # Model Card for Model ID  ## Model Details ### Model Description  - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.10.0

fleh/stage_model

fleh

2024-06-27T20:19:58Z

0

null

[ "region:us" ]

null

2024-06-27T20:19:58Z

Entry not found

Rupesh2/Llama-3-uncensored-dare

Rupesh2

2024-06-27T20:20:40Z

0

null

[ "region:us" ]

null

2024-06-27T20:20:40Z

Entry not found

Mananb141/Gaip

Mananb141

2024-06-27T20:26:22Z

0

null

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

null

2024-06-27T20:23:02Z

--- title: Car Parts Damage Detection emoji: 😻 colorFrom: gray colorTo: green sdk: gradio sdk_version: 3.11.0 app_file: app.py pinned: false license: mit --- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

gaelafoxuk/LoraPonyXL

gaelafoxuk

2024-06-28T19:54:03Z

0

null

[ "region:us" ]

null

2024-06-27T20:26:31Z

Entry not found

ekaterina-blatova-jb/model_lr1e-4_old_scheduler_with_t_max_275_v2

ekaterina-blatova-jb

2024-06-27T20:29:23Z

0

transformers

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

text-generation

2024-06-27T20:27:50Z

--- {} --- ## Evaluation results Validation loss on the whole input: 0.8595233634114265 Validation loss on completion: 0.9250378025462851

amirmm03/Movie_Genre_Classifier

amirmm03

2024-06-27T20:28:36Z

0

transformers

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

text-classification

2024-06-27T20:28:14Z

--- 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]

csikasote/huggingface

csikasote

2024-06-27T20:32:58Z

0

null

[ "region:us" ]

null

2024-06-27T20:32:58Z

Entry not found

habulaj/7325453667

habulaj

2024-06-27T20:34:54Z

0

null

[ "region:us" ]

null

2024-06-27T20:34:43Z

Entry not found

Maxivi/SDXLLightning

Maxivi

2024-06-28T19:01:48Z

0

null

[ "region:us" ]

null

2024-06-27T20:42:27Z

Entry not found

dOXINHO/srdoxinhoa

dOXINHO

2024-06-27T20:43:22Z

0

null

[ "region:us" ]

null

2024-06-27T20:43:22Z

Entry not found

AliAvd/Movie_Genre_Classifier

AliAvd

2024-06-27T20:46:36Z

0

transformers

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

null

2024-06-27T20:46:09Z

--- 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]

Solux77/Zadani

Solux77

2024-06-27T20:46:25Z

0

null

[ "doi:10.57967/hf/2634", "license:cc-by-nc-2.0", "region:us" ]

null

2024-06-27T20:46:25Z

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

Suchae/test-finetuned

Suchae

2024-06-27T20:47:39Z

0

transformers

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

null

2024-06-27T20:46:59Z

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

yuan-yang/Tiger-PJ-8B

yuan-yang

2024-06-27T22:52:01Z

0

null

[ "safetensors", "arxiv:2406.13764", "license:apache-2.0", "region:us" ]

null

2024-06-27T20:48:13Z

--- license: apache-2.0 --- # Tiger Model Card ## Model details Tactic-guided reasoner (Tiger) is a language model that solves *reasoning in the wild* task proposed in paper [Can LLMs Reason in the Wild with Programs](https://arxiv.org/abs/2406.13764). It is trained by fine-tuning the LLaMA3-8B model on the [ReWild](https://huggingface.co/datasets/yuan-yang/ReWild) dataset. **Model type:** This repo contains the LoRA delta weights for `Tiger-PJ-8B` We also provide the delta weights of other versions: - [Tiger-Routing-8B](https://huggingface.co/yuan-yang/Tiger-Routing-8B/) - [Tiger-PJ-8B](https://huggingface.co/yuan-yang/Tiger-PJ-8B) - [Tiger-IPJ-8B](https://huggingface.co/yuan-yang/Tiger-IPJ-8B) **License:** Apache License 2.0 ## Using the model Check out how to use the model on our project page: https://github.com/gblackout/Reason-in-the-Wild/ **Primary intended uses:** Tiger is intended to be used for research. ## Citation ``` @article{yang2024can, title={Can LLMs Reason in the Wild with Programs?}, author={Yang, Yuan and Xiong, Siheng and Payani, Ali and Shareghi, Ehsan and Fekri, Faramarz}, journal={arXiv preprint arXiv:2406.13764}, year={2024} } ```

yuan-yang/Tiger-IPJ-8B

yuan-yang

2024-06-27T22:52:56Z

0

null

[ "safetensors", "arxiv:2406.13764", "license:apache-2.0", "region:us" ]

null

2024-06-27T20:48:34Z

--- license: apache-2.0 --- # Tiger Model Card ## Model details Tactic-guided reasoner (Tiger) is a language model that solves *reasoning in the wild* task proposed in paper [Can LLMs Reason in the Wild with Programs](https://arxiv.org/abs/2406.13764). It is trained by fine-tuning the LLaMA3-8B model on the [ReWild](https://huggingface.co/datasets/yuan-yang/ReWild) dataset. **Model type:** This repo contains the LoRA delta weights for `Tiger-IPJ-8B` We also provide the delta weights of other versions: - [Tiger-Routing-8B](https://huggingface.co/yuan-yang/Tiger-Routing-8B/) - [Tiger-PJ-8B](https://huggingface.co/yuan-yang/Tiger-PJ-8B) - [Tiger-IPJ-8B](https://huggingface.co/yuan-yang/Tiger-IPJ-8B) **License:** Apache License 2.0 ## Using the model Check out how to use the model on our project page: https://github.com/gblackout/Reason-in-the-Wild/ **Primary intended uses:** Tiger is intended to be used for research. ## Citation ``` @article{yang2024can, title={Can LLMs Reason in the Wild with Programs?}, author={Yang, Yuan and Xiong, Siheng and Payani, Ali and Shareghi, Ehsan and Fekri, Faramarz}, journal={arXiv preprint arXiv:2406.13764}, year={2024} } ```

yuan-yang/Tiger-Routing-8B

yuan-yang

2024-06-27T22:50:33Z

0

null

[ "safetensors", "arxiv:2406.13764", "license:apache-2.0", "region:us" ]

null

2024-06-27T20:49:06Z

--- license: apache-2.0 --- # Tiger Model Card ## Model details Tactic-guided reasoner (Tiger) is a language model that solves *reasoning in the wild* task proposed in paper [Can LLMs Reason in the Wild with Programs](https://arxiv.org/abs/2406.13764). It is trained by fine-tuning the LLaMA3-8B model on the [ReWild](https://huggingface.co/datasets/yuan-yang/ReWild) dataset. **Model type:** This repo contains the LoRA delta weights for `Tiger-Routing-8B` We also provide the delta weights of other versions: - [Tiger-Routing-8B](https://huggingface.co/yuan-yang/Tiger-Routing-8B/) - [Tiger-PJ-8B](https://huggingface.co/yuan-yang/Tiger-PJ-8B) - [Tiger-IPJ-8B](https://huggingface.co/yuan-yang/Tiger-IPJ-8B) **License:** Apache License 2.0 ## Using the model Check out how to use the model on our project page: https://github.com/gblackout/Reason-in-the-Wild/ **Primary intended uses:** Tiger is intended to be used for research. ## Citation ``` @article{yang2024can, title={Can LLMs Reason in the Wild with Programs?}, author={Yang, Yuan and Xiong, Siheng and Payani, Ali and Shareghi, Ehsan and Fekri, Faramarz}, journal={arXiv preprint arXiv:2406.13764}, year={2024} } ```

Litzy619/MIS0626T6F200200

Litzy619

2024-06-27T20:49:13Z

0

null

[ "region:us" ]

null

2024-06-27T20:49:13Z

Entry not found

sulph/quasarcake

sulph

2024-06-28T11:05:33Z

0

1

null

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

null

2024-06-27T20:54:58Z

--- license: openrail ---

louistichelman/controlnet_streetview_segmentation_city2

louistichelman

2024-06-27T20:56:29Z

0

null

[ "region:us" ]

null

2024-06-27T20:56:29Z

Entry not found

sparsh35/deepseekmathslastft

sparsh35

2024-06-27T20:56:33Z

0

null

[ "region:us" ]

null

2024-06-27T20:56:33Z

Entry not found

Muradn/Han_Kanal-Oguzhan_Bostan

Muradn

2024-06-27T21:06:27Z

0

null

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

null

2024-06-27T21:05:15Z

--- license: openrail++ ---

valerielucro/mistral_gsm8k_preference_dataset_v2.1

valerielucro

2024-06-27T21:08:59Z

0

transformers

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

null

2024-06-27T21:08:22Z

--- 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]

howarudo/paligemma-3b-pt-224-vqa-continue-ft-5

howarudo

2024-06-27T21:10:56Z

0

transformers

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

null

2024-06-27T21:10:37Z

--- 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]

arhanovich/ds_3000gb

arhanovich

2024-06-28T23:28:06Z

0

null

[ "region:us" ]

null

2024-06-27T21:12:59Z

Entry not found

habulaj/5423391019

habulaj

2024-06-27T21:15:38Z

0

null

[ "region:us" ]

null

2024-06-27T21:15:28Z

Entry not found

habulaj/182895157431

habulaj

2024-06-27T21:15:45Z

0

null

[ "region:us" ]

null

2024-06-27T21:15:36Z

Entry not found

ycfNTU/B_hope_lora_llama7b

ycfNTU

2024-06-27T21:18:19Z

0

transformers

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

null

2024-06-27T21:18:10Z

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

habulaj/36793907

habulaj

2024-06-27T21:21:21Z

0

null

[ "region:us" ]

null

2024-06-27T21:21:19Z

Entry not found

Darshandev/Future-Insight-Predicto

Darshandev

2024-06-27T21:24:33Z

0

null

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

null

2024-06-27T21:23:31Z

--- license: apache-2.0 --- ## Future Insight Predictor This Streamlit application helps you predict future values based on historical data in a CSV file. It offers various machine learning algorithms to choose from and provides informative visualizations to assess model performance. ### Getting Started 1. **Prerequisites:** - Python 3.x - Streamlit: `pip install streamlit` - Pandas: `pip install pandas` - scikit-learn: `pip install scikit-learn` - matplotlib: `pip install matplotlib` - seaborn: `pip install seaborn` 2. **Run the app:** - Save the code as `app.py`. - Open a terminal, navigate to the directory containing the file, and run: ```bash streamlit run app.py ``` ### How it Works 1. Upload a CSV file containing your historical data. 2. The app will display a preview of the data. 3. Preprocessing is applied to format the data for modeling. 4. Select the features (independent variables) and target variable (dependent variable) for prediction. 5. Choose a prediction task based on your data domain (e.g., Stock Sale, Real Estate Prices). 6. Select a machine learning algorithm for prediction. 7. Click "Train and Evaluate" to train the model and view the results. ### Output - The predicted value for the next month. - Model accuracy score and cross-validation scores for evaluation. - Visualization comparing actual vs predicted values, highlighting overestimations and underestimations. ### Note This is a basic implementation and can be further enhanced with additional features and functionalities based on your specific needs. ### Contributing Feel free to fork the repository and submit pull requests with improvements or additional features!

sahielbose/plant-detection-model

sahielbose

2024-06-27T21:24:08Z

0

null

[ "region:us" ]

null

2024-06-27T21:24:08Z

Entry not found

whizzzzkid/whizzzzkid_235_4

whizzzzkid

2024-06-27T21:25:58Z

0

transformers

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

text-generation

2024-06-27T21:24:14Z

Entry not found

pursuitofds/finetuned_qa_llama3_8b_qlora_model

pursuitofds

2024-06-28T14:47:09Z

0

Llama-3-8B-peft-QA-QLoRa

[ "Llama-3-8B-peft-QA-QLoRa", "safetensors", "base_model:pursuitofds/finetuned_qa_llama3_8b_qlora_model", "region:us" ]

null

2024-06-27T21:24:32Z

--- library_name: Llama-3-8B-peft-QA-QLoRa base_model: pursuitofds/finetuned_qa_llama3_8b_qlora_model --- # Model Card for Model ID  The model is finetuned on the SQUAD2 dataset using QLora. - **Model type:** [More Information Needed] - **Language(s) (NLP):** English - **Finetuned from model [optional]:** Llama3-8B ## Uses ```python from transformers import AutoModelForQuestionAnswering, AutoTokenizer model = AutoModelForQuestionAnswering.from_pretrained("pursuitofds/finetuned_qa_llama3_8b_qlora_model") tokenizer = AutoTokenizer.from_pretrained("pursuitofds/finetuned_qa_llama3_8b_qlora_model") inputs = tokenizer("What is the capital of France?", return_tensors="pt") outputs = model(**inputs) answer_start = outputs.start_logits.argmax() answer_end = outputs.end_logits.argmax() + 1 answer = tokenizer.convert_tokens_to_string(tokenizer.convert_ids_to_tokens(inputs.input_ids[0][answer_start:answer_end])) print(answer) # Should print "Paris"

whizzzzkid/whizzzzkid_233_1

whizzzzkid

2024-06-27T21:26:49Z

0

transformers

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

text-generation

2024-06-27T21:25:03Z

Entry not found

jessylin/vllama3

jessylin

2024-06-28T01:01:41Z

0

null

[ "region:us" ]

null

2024-06-27T21:25:26Z

Entry not found

mabrouk/first-model

mabrouk

2024-06-27T21:27:47Z

0

null

[ "region:us" ]

null

2024-06-27T21:27:47Z

Entry not found

NRbones/Hancock

NRbones

2024-06-27T21:38:08Z

0

null

[ "region:us" ]

null

2024-06-27T21:27:51Z

Entry not found

habulaj/542318517965

habulaj

2024-06-27T21:29:27Z

0

null

[ "region:us" ]

null

2024-06-27T21:29:24Z

Entry not found

shiromiya/fairseq-hubert-portuguese

shiromiya

2024-06-29T02:15:18Z

0

1

null

[ "region:us" ]

null

2024-06-27T21:29:37Z

Entry not found

habulaj/328166294230

habulaj

2024-06-27T21:30:29Z

0

null

[ "region:us" ]

null

2024-06-27T21:30:26Z

Entry not found

whizzzzkid/whizzzzkid_236_5

whizzzzkid

2024-06-27T21:32:49Z

0

transformers

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

text-generation

2024-06-27T21:31:04Z

Entry not found

Arodrigo/temp001

Arodrigo

2024-06-27T21:31:35Z

0

transformers

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

null

2024-06-27T21:31:27Z

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

Pra-tham/whisper-peft-full-labelled

Pra-tham

2024-06-28T06:54:04Z

0

transformers

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

null

2024-06-27T21:31:57Z

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

JEFFERSONMUSIC/BRUNEIHWT1996

JEFFERSONMUSIC

2024-06-27T21:34:00Z

0

null

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

null

2024-06-27T21:32:52Z

--- license: apache-2.0 ---

huggingfacepremium/autotrain-t5jjv-fxr8g

huggingfacepremium

2024-06-27T23:16:58Z

0

transformers

[ "transformers", "tensorboard", "safetensors", "autotrain", "text-generation-inference", "text-generation", "peft", "conversational", "dataset:huggingfacepremium/kober1", "base_model:microsoft/Phi-3-mini-4k-instruct", "license:other", "endpoints_compatible", "region:us" ]

text-generation

2024-06-27T21:33:44Z

--- tags: - autotrain - text-generation-inference - text-generation - peft library_name: transformers base_model: microsoft/Phi-3-mini-4k-instruct widget: - messages: - role: user content: What is your favorite condiment? license: other datasets: - huggingfacepremium/kober1 --- # Model Trained Using AutoTrain This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain). # Usage ```python from transformers import AutoModelForCausalLM, AutoTokenizer model_path = "PATH_TO_THIS_REPO" tokenizer = AutoTokenizer.from_pretrained(model_path) model = AutoModelForCausalLM.from_pretrained( model_path, device_map="auto", torch_dtype='auto' ).eval() # Prompt content: "hi" messages = [ {"role": "user", "content": "hi"} ] input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt') output_ids = model.generate(input_ids.to('cuda')) response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True) # Model response: "Hello! How can I assist you today?" print(response) ```

thibautweber/fraud_detection_updated

thibautweber

2024-06-27T21:34:40Z

0

transformers

[ "transformers", "safetensors", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:unsloth/mistral-7b-instruct-v0.2-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

2024-06-27T21:34:26Z

--- base_model: unsloth/mistral-7b-instruct-v0.2-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - **Developed by:** thibautweber - **License:** apache-2.0 - **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-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)

habulaj/327396293447

habulaj

2024-06-27T21:36:53Z

0

null

[ "region:us" ]

null

2024-06-27T21:36:50Z

Entry not found

habulaj/8001357917

habulaj

2024-06-27T21:42:04Z

0

null

[ "region:us" ]

null

2024-06-27T21:41:57Z

Entry not found

habulaj/542342517989

habulaj

2024-06-27T21:44:15Z

0

null

[ "region:us" ]

null

2024-06-27T21:44:12Z

Entry not found

hammadsaleem/sdqn-SpaceInvadersNoFrameskip-v4

hammadsaleem

2024-06-27T21:51:49Z

0

null

[ "region:us" ]

null

2024-06-27T21:51:49Z

Entry not found

Coolwowsocoolwow/Waluigi

Coolwowsocoolwow

2024-06-27T21:55:09Z

0

null

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

null

2024-06-27T21:52:21Z

--- license: openrail ---

Tonygab/Male

Tonygab

2024-06-27T21:54:26Z

0

null

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

null

2024-06-27T21:53:20Z

--- license: openrail ---

habulaj/1189616542

habulaj

2024-06-27T21:54:34Z

0

null

[ "region:us" ]

null

2024-06-27T21:54:27Z

Entry not found

habulaj/318093284580

habulaj

2024-06-27T21:56:37Z

0

null

[ "region:us" ]

null

2024-06-27T21:56:35Z

Entry not found

Hnhasni/Voice

Hnhasni

2024-06-27T21:59:34Z

0

null

[ "region:us" ]

null

2024-06-27T21:59:34Z

Entry not found

X0x0G/Lisa_Mimi_Capstone

X0x0G

2024-06-27T22:00:09Z

0

null

[ "region:us" ]

null

2024-06-27T22:00:09Z

Entry not found

tokare163/Bdjsjzjzjxjx

tokare163

2024-06-27T22:01:39Z

0

null

[ "region:us" ]

null

2024-06-27T22:01:39Z

Entry not found

ayse0/garbage_classification_model

ayse0

2024-06-27T22:03:55Z

0

null

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

null

2024-06-27T22:03:55Z

--- license: mit ---

asemane/Movie_Genre_Classifier

asemane

2024-06-27T22:24:16Z

0

transformers

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

null

2024-06-27T22:04:25Z

--- 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]

AdamKasumovic/phi3-mini-4k-instruct-bactrian-x-en-100-percent-med-perplexity-mmlu_ck

AdamKasumovic

2024-06-27T22:08:44Z

0

transformers

[ "transformers", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:unsloth/Phi-3-mini-4k-instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

2024-06-27T22:08:44Z

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

habulaj/61099187815

habulaj

2024-06-27T22:11:26Z

0

null

[ "region:us" ]

null

2024-06-27T22:11:24Z

Entry not found

habulaj/11033485185

habulaj

2024-06-27T22:11:31Z

0

null

[ "region:us" ]

null

2024-06-27T22:11:28Z

Entry not found

tctrautman/20240627-kibbe-prod-with-no-celeb-data

tctrautman

2024-06-27T22:12:55Z

0

null

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

null

2024-06-27T22:12:51Z

--- license: apache-2.0 base_model: HuggingFaceM4/idefics2-8b tags: - generated_from_trainer model-index: - name: 20240627-kibbe-prod-with-no-celeb-data 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/8aq6w9lt) # 20240627-kibbe-prod-with-no-celeb-data 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: 0.0289 ## 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 | |:-------------:|:------:|:----:|:---------------:| | 0.9221 | 0.5005 | 510 | 0.0337 | | 0.5426 | 1.0010 | 1020 | 0.0324 | | 0.6505 | 1.5015 | 1530 | 0.0289 | ### Framework versions - Transformers 4.43.0.dev0 - Pytorch 2.1.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1

sankar-a/llm_test

sankar-a

2024-06-27T22:14:45Z

0

null

[ "region:us" ]

null

2024-06-27T22:14:45Z

Entry not found

Heruss/FDA

Heruss

2024-06-27T22:17:37Z

0

null

[ "region:us" ]

null

2024-06-27T22:16:48Z

Entry not found

Heruss/LRSADAWNG

Heruss

2024-06-27T22:19:18Z

0

null

[ "region:us" ]

null

2024-06-27T22:18:34Z

Entry not found

howarudo/paligemma-3b-pt-224-vqa-continue-ft-6

howarudo

2024-06-27T22:19:26Z

0

transformers

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

null

2024-06-27T22:19:05Z

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

ChenmieNLP/SELM-Llama-3-8B-Instruct-iter-1

ChenmieNLP

2024-06-27T22:19:10Z

0

null

[ "region:us" ]

null

2024-06-27T22:19:10Z

Entry not found

nglguarino/my-nlp-gemma-model2

nglguarino

2024-06-27T22:20:06Z

0

transformers

[ "transformers", "safetensors", "text-generation-inference", "unsloth", "gemma", "trl", "en", "base_model:unsloth/gemma-2b-it-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

2024-06-27T22:19:57Z

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

AdamKasumovic/phi3-mini-4k-instruct-bactrian-x-en-100-percent-low-perplexity-mmlu_ck

AdamKasumovic

2024-06-27T22:22:18Z

0

transformers

[ "transformers", "safetensors", "mistral", "text-generation", "text-generation-inference", "unsloth", "trl", "conversational", "en", "base_model:unsloth/Phi-3-mini-4k-instruct-bnb-4bit", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-generation

2024-06-27T22:20:15Z

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

habulaj/10219177243

habulaj

2024-06-27T22:21:11Z

0

null

[ "region:us" ]

null

2024-06-27T22:21:09Z

Entry not found

kevin009/babyllama07

kevin009

2024-06-28T00:49:24Z

0

transformers

[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:TinyLlama/TinyLlama_v1.1_math_code", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

2024-06-27T22:24:16Z

--- language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl base_model: TinyLlama/TinyLlama_v1.1_math_code --- # Uploaded model - **Developed by:** kevin009 - **License:** apache-2.0 - **Finetuned from model :** TinyLlama/TinyLlama_v1.1_math_code 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)

Arodrigo/temp002

Arodrigo

2024-06-27T22:25:48Z

0

transformers

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

null

2024-06-27T22:25:41Z

--- 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]

Coolwowsocoolwow/WAHHH

Coolwowsocoolwow

2024-06-27T22:31:55Z

0

null

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

null

2024-06-27T22:30:14Z

--- license: openrail ---

Litzy619/MIS0627T1F200200

Litzy619

2024-06-27T22:39:03Z

0

null

[ "region:us" ]

null

2024-06-27T22:39:03Z

Entry not found

Ramikan-BR/TiamaPY-LORA-v38

Ramikan-BR

2024-06-27T22:44:55Z

0

transformers

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

null

2024-06-27T22:44:25Z

--- base_model: unsloth/tinyllama-chat-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - **Developed by:** Ramikan-BR - **License:** apache-2.0 - **Finetuned from model :** unsloth/tinyllama-chat-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)

ness321/Indonesia-BERT-QA

ness321

2024-06-27T22:44:51Z

0

null

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

null

2024-06-27T22:44:51Z

--- license: other license_name: vaness license_link: LICENSE ---

Enkeeper/Gemma_2B_TaskInstruct_Unsloth_LORA

Enkeeper

2024-06-27T22:45:32Z

0

null

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

null

2024-06-27T22:45:19Z

--- license: gemma ---

mpa21/video1

mpa21

2024-06-27T22:51:39Z

0

null

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

null

2024-06-27T22:48:38Z

--- license: openrail ---

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

abdiharyadi

2024-06-27T22:54:26Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-27T22:52:38Z

Entry not found

baseten/HR-finetune

baseten

2024-06-27T22:55:21Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-27T22:54:59Z

Entry not found

mmbutera/moka

mmbutera

2024-06-27T22:56:33Z

0

null

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

null

2024-06-27T22:55:43Z

--- license: openrail ---

estepadilla/sne_classifier

estepadilla

2024-06-28T16:16:42Z

0

null

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

null

2024-06-27T22:59:56Z

--- license: mit ---

wopi/conv

wopi

2024-07-02T03:47:58Z

0

null

[ "region:us" ]

null

2024-06-27T23:05:38Z

Entry not found

anonymous55/blip-celeba-1000-100

anonymous55

2024-06-27T23:07:00Z

0

transformers

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

text2text-generation

2024-06-27T23:06:37Z

--- 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]

Ghareeb-M/my-finetuned-banking77-distilbert

Ghareeb-M

2024-07-01T17:02:31Z

0

transformers

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

text-classification

2024-06-27T23:15:44Z

Entry not found

ycfNTU/B_fear_lora_llama7b

ycfNTU

2024-06-27T23:21:30Z

0

transformers

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

null

2024-06-27T23:21:20Z

--- 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]

abdiharyadi/indoamrbart-mbart-triple-ft-parser-no-nst-32-eps

abdiharyadi

2024-06-27T23:25:18Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-27T23:23:33Z

Entry not found

habulaj/242516214136

habulaj

2024-06-27T23:24:29Z

0

null

[ "region:us" ]

null

2024-06-27T23:24:23Z

Entry not found

habulaj/55296800

habulaj

2024-06-27T23:25:00Z

0

null

[ "region:us" ]

null

2024-06-27T23:24:55Z

Entry not found

fifala/08-fifa-06-28-01

fifala

2024-06-27T23:28:10Z

0

transformers

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

text-generation

2024-06-27T23:25:39Z

Entry not found

Belvannn/Tyrone

Belvannn

2024-06-27T23:27:21Z

0

null

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

null

2024-06-27T23:26:23Z

--- license: openrail ---

habulaj/49835951

habulaj

2024-06-27T23:26:56Z

0

null

[ "region:us" ]

null

2024-06-27T23:26:49Z

Entry not found

howarudo/paligemma-3b-pt-224-vqa-continue-ft-7

howarudo

2024-06-27T23:27:50Z

0

transformers

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

null

2024-06-27T23:27:31Z

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

habulaj/236303207665

habulaj

2024-06-27T23:28:10Z

0

null

[ "region:us" ]

null

2024-06-27T23:28:01Z

Entry not found

adamo1139/Yi-34B-200K-HESOYAM-TURTLE-2606-5bpw-exl2

adamo1139

2024-06-27T23:41:12Z

0

transformers

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

text-generation

2024-06-27T23:28:20Z

--- license: apache-2.0 ---