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
Granther/phi3-fine-tuning-files	Granther	2024-06-27T03:54:09Z	0	null	[ "region:us" ]	null	2024-06-27T03:50:30Z	Entry not found
tstars/alpaca_lora	tstars	2024-06-27T03:50:40Z	0	null	[ "region:us" ]	null	2024-06-27T03:50:40Z	Entry not found
habulaj/1097311636	habulaj	2024-06-27T03:51:10Z	0	null	[ "region:us" ]	null	2024-06-27T03:51:05Z	Entry not found
danielhenel/smishing-detection-mistral-7b-instruct-v0.3	danielhenel	2024-06-27T03:53:51Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T03:53:09Z	--- 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]
habulaj/522734496225	habulaj	2024-06-27T03:54:11Z	0	null	[ "region:us" ]	null	2024-06-27T03:54:08Z	Entry not found
Ksgk-fy/phillipine_customer_ooc_patch_v4.0_Maria_ooc_patch_v1	Ksgk-fy	2024-07-01T06:53:16Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-27T03:57:28Z	Entry not found
ayousanz/Style-Bert-VITS2-jp_extra_large	ayousanz	2024-06-27T04:02:34Z	7	null	[ "region:us" ]	null	2024-06-27T04:00:50Z	Style-Bert-VITS2用事前学習モデルjp_extra_large_Ver20240627_20240630 ====許可している内容==== １：githubやhuggingface等の不特定多数がダウンロード可能なサイトへのアップロード（転載）２：この事前学習モデルは俺 or 私が作った！という自作発言及び、自身の成果物としての宣伝・配布・販売３：禁止事項の改変やライセンスの変更（自作発言をする場合は自由に変更して構わない） ====禁止事項==== １：転載時に転載元を記載しない。＊悪意あるサイトへの誘導を防ぐ為。２：転載時に転載元のアップロード者及び開発者に関する内容を記載しない。＊転載しただけの人が開発者と混同されないようにするため。＊＊自作発言をした人が出てきた場合に混沌とするため。 ====使用上の注意==== 使用可能な記号として:　;　=　#　<　>　^　(　)　*の計10個を追加しています。追加学習に用いるデータが多い場合に差が出やすいです。 VRAM16GB以上の環境で学習をするのを想定しています。 G_XXXXX.pthのサイズは約1.4GB XXXX_eYYY_sZZZZZZ.safetensorsのサイズは約400MB ====使い方==== 各フォルダーに上書き。
Pingkkkkklksl/my-pretrained-model	Pingkkkkklksl	2024-06-27T04:01:16Z	0	null	[ "license:mit", "region:us" ]	null	2024-06-27T04:01:16Z	--- license: mit ---
nachus2/modeltest	nachus2	2024-06-27T04:03:32Z	0	asteroid	[ "asteroid", "biology", "chemistry", "climate", "audio-classification", "ar", "license:artistic-2.0", "region:us" ]	audio-classification	2024-06-27T04:01:57Z	--- license: artistic-2.0 language: - ar metrics: - accuracy - bleu - character library_name: asteroid pipeline_tag: audio-classification tags: - biology - chemistry - climate ---
ariG23498/zephyr-7b-gemma-v0.1	ariG23498	2024-06-27T04:04:14Z	0	null	[ "region:us" ]	null	2024-06-27T04:04:14Z	Entry not found
TioPanda/pandev-blocks-v4	TioPanda	2024-06-27T04:07:33Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:unsloth/llama-3-8b-Instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T04:06:56Z	--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: TioPanda - License: apache-2.0 - Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
smokewulf/Devika	smokewulf	2024-06-27T04:07:47Z	0	null	[ "region:us" ]	null	2024-06-27T04:07:47Z	Entry not found
geraldabrhm/llama-3-8b-regular-simplecontext-32lora-lr8_5-32batch	geraldabrhm	2024-06-27T05:57:03Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-27T04:08:47Z	Entry not found
EmersonKaleb/chatbot	EmersonKaleb	2024-06-27T04:09:19Z	0	null	[ "region:us" ]	null	2024-06-27T04:09:18Z	Entry not found
Litzy619/MIS0626T4F200200	Litzy619	2024-06-27T10:38:51Z	0	null	[ "region:us" ]	null	2024-06-27T04:11:04Z	Entry not found
vedkulkarni/whisper-base-hi	vedkulkarni	2024-06-27T04:20:43Z	0	null	[ "region:us" ]	null	2024-06-27T04:20:43Z	Entry not found
Haary/USK_Mistral_7B_Unsloth	Haary	2024-06-27T05:12:41Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "mistral", "trl", "en", "id", "dataset:Haary/QA_USK_dataset", "base_model:Ichsan2895/Merak-7B-v4", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T04:23:37Z	--- base_model: Ichsan2895/Merak-7B-v4 language: - en - id license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl datasets: - Haary/QA_USK_dataset --- # Uploaded model - Developed by: Haary - License: apache-2.0 - Finetuned from Indonesia model : [Ichsan2895/Merak-7B-v4](https://huggingface.co/Ichsan2895/Merak-7B-v4) - Base model : [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
PhillipGuo/hp-lat-llama-No_PCA-epsilon3.0-pgd_layer12-def_layer13_14_15-wikitext-fullrank-97	PhillipGuo	2024-06-27T04:24:06Z	0	null	[ "region:us" ]	null	2024-06-27T04:24:06Z	Entry not found
Azaz666/mt5-small-finetuned-CEP	Azaz666	2024-06-27T04:25:13Z	0	null	[ "region:us" ]	null	2024-06-27T04:25:13Z	Entry not found
PhillipGuo/hp-lat-llama-No_PCA-epsilon0.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-99	PhillipGuo	2024-06-27T04:26:02Z	0	null	[ "region:us" ]	null	2024-06-27T04:26:02Z	Entry not found
starnet/15-star21-06-27	starnet	2024-06-27T04:34:12Z	0	null	[ "any-to-any", "omega", "omegalabs", "bittensor", "agi", "license:mit", "region:us" ]	null	2024-06-27T04:26:54Z	--- license: mit tags: - any-to-any - omega - omegalabs - bittensor - agi --- This is an Any-to-Any model checkpoint for the OMEGA Labs x Bittensor Any-to-Any subnet. Check out the [git repo](https://github.com/omegalabsinc/omegalabs-anytoany-bittensor) and find OMEGA on X: [@omegalabsai](https://x.com/omegalabsai).
camenduru/MeshAnything	camenduru	2024-06-27T04:29:21Z	0	null	[ "region:us" ]	null	2024-06-27T04:28:08Z	Entry not found
PhillipGuo/hp-lat-llama-No_PCA-epsilon1.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-100	PhillipGuo	2024-06-27T04:30:14Z	0	null	[ "region:us" ]	null	2024-06-27T04:30:14Z	Entry not found
PhillipGuo/hp-lat-llama-No_PCA-epsilon0.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-100	PhillipGuo	2024-06-27T04:31:26Z	0	null	[ "region:us" ]	null	2024-06-27T04:31:26Z	Entry not found
PhillipGuo/hp-lat-llama-No_PCA-epsilon3.0-pgd_layer12-def_layer13_14_15-wikitext-fullrank-100	PhillipGuo	2024-06-27T04:32:33Z	0	null	[ "region:us" ]	null	2024-06-27T04:32:32Z	Entry not found
PhillipGuo/hp-lat-llama-No_PCA-epsilon0.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-96	PhillipGuo	2024-06-27T04:33:51Z	0	null	[ "region:us" ]	null	2024-06-27T04:33:51Z	Entry not found
eoinf/unlearning_saes	eoinf	2024-06-27T06:55:05Z	0	null	[ "region:us" ]	null	2024-06-27T04:34:23Z	Entry not found
GrowingApple/llama-3-8B-medical-kor-chat_test	GrowingApple	2024-06-27T04:43:52Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T04:35:17Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
PhillipGuo/hp-lat-llama-No_PCA-epsilon1.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-99	PhillipGuo	2024-06-27T04:37:30Z	0	null	[ "region:us" ]	null	2024-06-27T04:37:30Z	Entry not found
GraydientPlatformAPI/loras-jun27b	GraydientPlatformAPI	2024-06-27T04:43:04Z	0	null	[ "region:us" ]	null	2024-06-27T04:38:43Z	Entry not found
nan7892/Yinan_test_ppo_7b	nan7892	2024-06-27T04:40:45Z	1	null	[ "license:apache-2.0", "region:us" ]	null	2024-06-27T04:40:45Z	--- license: apache-2.0 ---
Azaz666/t5-base-finetuned-CEP	Azaz666	2024-06-27T04:42:10Z	0	null	[ "region:us" ]	null	2024-06-27T04:42:10Z	Entry not found
valerielucro/mistral_gsm8k_beta_0.4_epoch3	valerielucro	2024-06-27T04:52:08Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T04:51:48Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- 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]
Surekel/training	Surekel	2024-06-27T05:04:36Z	0	null	[ "license:mit", "region:us" ]	null	2024-06-27T04:52:02Z	--- license: mit ---
foduucom/resume-extractor	foduucom	2024-06-27T05:19:58Z	0	null	[ "resume", "extractor", "resume extractor", "pdf", "extract", "cv parser", "pdf extraction", "document analysis", "unstructured document", "DataProcessing", "TextToJSON", "resume parser", "resume information extractor", "resume data extraction", "en", "region:us" ]	null	2024-06-27T04:54:51Z	--- language: - en tags: - resume - extractor - resume extractor - pdf - extract - cv parser - pdf extraction - document analysis - unstructured document - DataProcessing - TextToJSON - resume parser - resume information extractor - resume data extraction --- # PDF Resume Information Extractor ## Description This Python script extracts information from PDF resumes and converts it into a structured JSON format using the Ollama language model. It's designed to automate the process of parsing resumes and extracting key details, making it easier for HR departments, recruiters, and organizations to process large volumes of applications efficiently. What sets this script apart is its ability to handle various resume formats and styles. It uses a predefined JSON template to ensure consistent output structure, making it easier to integrate with other systems or databases. The script is designed to be flexible, allowing for customization of the output format and the underlying language model. We invite you to explore the potential of this script and its data extraction capabilities. For those interested in harnessing its power or seeking further collaboration, we encourage you to reach out to us or contribute to the project on GitHub. Your input drives our continuous improvement, as we collectively pave the way towards enhanced data extraction and document analysis. - Developed by: FODUU AI - Model type: Extraction - Task: Resume Parsing and Information Extraction ### Supported Output Fields The exact fields depend on the JSON template which have includes the following fields: ['name', 'email', 'phone_1', 'phone_2', 'address', 'city', 'highest_education', 'is_fresher','is_student', 'professional_experience_in_years', 'skills' ,'linkedin' , 'applied_for_profile', 'education', 'professional_experience'] ## Uses ### Direct Use The Resume Information Extractor can be directly used for parsing resume PDFs and extracting structured information. It's particularly useful for HR departments, recruitment agencies, or any organization that deals with large volumes of resumes. ### Downstream Use The extracted information can be used for various downstream tasks such as candidate matching, resume scoring, or populating applicant tracking systems. ### Out-of-Scope Use The model is not designed for tasks unrelated to resume parsing or for processing documents that are not resumes. ## Risks, and Limitations The Resume Information Extractor may have some limitations and risks, including: - Performance may vary based on the format and structure of the input resume. - The quality of extraction depends on the capabilities of the underlying Ollama model. - It may struggle with highly unconventional resume formats or non-English resumes. - The script does not verify the accuracy of the information in the resume. ### Recommendations Users should be aware of the script's limitations and potential risks. It's recommended to manually verify the extracted information for critical applications. Further testing and validation are advised for specific use cases to evaluate its performance accurately. ## How to Get Started with the Model To begin using the Resume Information Extractor, follow these steps: 1. Clone this repository: ```bash git clone https://huggingface.co/nehulagrawal/resume-extractor ``` 2. Install the required packages: ```bash pip install langchain_community pdfminer.six ollama ``` or ```bash pip install -r requirements.txt ``` 3. Ensure you have Ollama set up and running with the "llama3" model. 4. Use this Python script: ```python from pdfminer.high_level import extract_text from json_helper import InputData as input def extract_text_from_pdf(pdf_path): return extract_text(pdf_path) text = extract_text_from_pdf(r'path/to/your/document/pdf') llm = input.llm() data = llm.invoke(input.input_data(text)) print(data) ``` ## Objective This script uses the Ollama language model to understand and extract information from resume text. The specific architecture depends on the Ollama model being used. ## Contact For inquiries and contributions, please contact us at [email protected]. ```bibtex @contact{foduu, author = {Foduu}, title = {Resume Extractor}, year = {2024} } ```
tomreichel/proof-repair-model	tomreichel	2024-06-27T04:55:36Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T04:55:24Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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(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]
tomreichel/proof-synthesis-model	tomreichel	2024-06-27T04:57:01Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T04:56:50Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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pig142857/cobra_mambaV2	pig142857	2024-07-02T03:08:35Z	0	null	[ "license:mit", "region:us" ]	null	2024-06-27T04:58:39Z	--- license: mit ---
DZERV/lonzodontknowgng	DZERV	2024-06-27T05:01:37Z	0	null	[ "license:openrail", "region:us" ]	null	2024-06-27T05:00:24Z	--- license: openrail ---
Keerthan40/Driver_Alert_System	Keerthan40	2024-06-27T06:27:24Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T05:02:47Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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lfnothing/code-search-net-tokenizer	lfnothing	2024-06-27T05:08:39Z	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T05:08:38Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
shannu999/hv	shannu999	2024-06-27T05:11:08Z	0	null	[ "region:us" ]	null	2024-06-27T05:11:08Z	Entry not found
haerxiluo/my-cv-boneage	haerxiluo	2024-06-27T05:45:39Z	0	null	[ "region:us" ]	null	2024-06-27T05:12:09Z	Entry not found
BigMitchell/puff_yfm	BigMitchell	2024-06-27T05:49:40Z	0	null	[ "region:us" ]	null	2024-06-27T05:14:21Z	Entry not found
firsthac/unauth	firsthac	2024-06-27T05:15:36Z	0	null	[ "region:us" ]	null	2024-06-27T05:15:36Z	Entry not found
alxcarln/esm2_t30_150M_UR50D-finetuned-localization	alxcarln	2024-06-27T05:16:38Z	0	null	[ "region:us" ]	null	2024-06-27T05:16:38Z	Entry not found
firsthac/unauth1	firsthac	2024-06-27T05:16:41Z	0	null	[ "region:us" ]	null	2024-06-27T05:16:41Z	Entry not found
alxcarln/esm2_t6_8M_UR50D-finetuned-localization	alxcarln	2024-06-27T05:20:37Z	0	null	[ "region:us" ]	null	2024-06-27T05:20:36Z	Entry not found
KhanLee0930/q-FrozenLake-v1-4x4-noSlippery	KhanLee0930	2024-06-27T05:21:45Z	0	null	[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2024-06-27T05:21:43Z	--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # Q-Learning Agent playing1 FrozenLake-v1 This is a trained model of a Q-Learning agent playing FrozenLake-v1 . ## Usage ```python model = load_from_hub(repo_id="KhanLee0930/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
KhanLee0930/Taxi-v3	KhanLee0930	2024-06-27T05:22:36Z	0	null	[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2024-06-27T05:22:34Z	--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: Taxi-v3 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.54 +/- 2.73 name: mean_reward verified: false --- # Q-Learning Agent playing1 Taxi-v3 This is a trained model of a Q-Learning agent playing Taxi-v3 . ## Usage ```python model = load_from_hub(repo_id="KhanLee0930/Taxi-v3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
Bodo121/Bodosa121	Bodo121	2024-06-27T05:30:16Z	0	null	[ "region:us" ]	null	2024-06-27T05:30:16Z	Entry not found
VKapseln475/Nexalyn41422	VKapseln475	2024-06-27T05:38:19Z	0	null	[ "region:us" ]	null	2024-06-27T05:31:53Z	# [NY] Nexalyn Danmark Erfaringer - Nexalyn Anmeldelser Dosis og Virker Officiel pris, køb [NY] Nexalyn Danmark Erfaringer At forbrænde fedt i besværlige områder er en udfordring for mange mennesker på deres vægttabsrejse. Dette stædige kropsfedt kan være frustrerende og svært at målrette mod med kost og motion alene. Nexaslim-tillægget kan dog give den løsning, du har ledt efter. ## [Klik her for at købe nu fra Nexalyn officielle hjemmeside](https://capsules24x7.com/nexalyn-danmark) ## Hvordan hjælper dette produkt dig med at øge dit energiniveau? Hvis du mangler energi og udholdenhed, kan Nexalyn testo booster-kapsler i Sydafrika være den løsning, du har ledt efter. Dette kraftfulde kosttilskud har ingredienser, der kan hjælpe med at booste energiniveauet og revitalisere din krop. Det kan virke ved at øge testosteronniveauet, hvilket kan føre til forbedret energi og vitalitet. Det kan også virke ved at forbedre libido og seksuel ydeevne. Produktet indeholder forbindelser, der kan øge produktionen af nitrogenoxid, som kan være med til at forbedre blodgennemstrømningen i hele kroppen, herunder til musklerne. Denne forbedrede cirkulation kan føre til øget energiniveau. Det kan understøtte hormonbalancen, samtidig med at det giver en naturlig kilde til antioxidanter, der kan fremme det generelle velvære. Nexalyn testosteron booster spiller en vigtig rolle i at understøtte sunde hormonniveauer i kroppen, samt fremme sund prostatafunktion, som begge kan bidrage til øget energiniveau. Ved at tilføje dette produkt til din daglige rutine, kan du opleve en mærkbar forbedring i dit overordnede energiniveau i løbet af dagen. Uanset om det er at håndtere opgaver på arbejdet eller nyde intime stunder med din partner, kan dette tillæg give dig det ekstra boost, du har brug for for at komme igennem. ## Hvordan forbedrer dette supplement din sensuelle ydeevne? Når det kommer til at forbedre din sensuelle ydeevne, er Nexalyn mandlig forbedring her for at hjælpe dig. Dette kraftfulde supplement kan øge din seksuelle energi og udholdenhed, så du kan få mere intense og tilfredsstillende oplevelser i soveværelset. ## [Klik her for at købe nu fra Nexalyn officielle hjemmeside](https://capsules24x7.com/nexalyn-danmark)
JefiRyan/llama-3-8b-gguf	JefiRyan	2024-06-27T05:34:49Z	0	null	[ "region:us" ]	null	2024-06-27T05:32:04Z	Entry not found
tuskbyte/raw_nld_v5_char_1	tuskbyte	2024-06-27T05:32:39Z	0	transformers	[ "transformers", "safetensors", "vits", "text-to-audio", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	text-to-audio	2024-06-27T05:32:29Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
ShapeKapseln33/Nexalyn23	ShapeKapseln33	2024-06-27T05:39:53Z	0	null	[ "region:us" ]	null	2024-06-27T05:35:12Z	[Offisiell] Nexalyn Anmeldelser: I en verden hvor vitalitet og ytelse ofte er synonymt med suksess, er det viktig å opprettholde topp fysisk form. For menn strekker dette seg ofte utover bare kondisjon til områder med vitalitet, virilitet og generelt velvære. Men ettersom alderen innhenter oss, kan ulike faktorer hemme vår evne til å opprettholde optimal ytelse og tilfredshet i disse rikene. [Klikk her for å kjøpe nå fra Nexalyns offisielle nettsted](https://ketogummies24x7.com/nexalyn-no) ##Introduksjon til Nexalyn Vil du ta dine seksuelle opplevelser til neste nivå? Hvis ja, se ikke lenger enn Nexalyn Testosterone Booster Formula, det revolusjonerende kosttilskuddet som skaper bølger i verden av seksuell helse. Hvis du noen gang har ønsket deg sterkere ereksjoner, økt sensuell appetitt og eksplosive orgasmer, så har du kommet til rett sted. I dag skal vi diskutere alt du trenger å vite om Nexalyn mannlige forsterkningstilskudd, fra den vitenskapelig støttede formelen til nøkkelingrediensene som vil hjelpe deg å øke din seksuelle ytelse. ##Vitenskapen bak Nexalyn Testo booster og hvordan den fungerer: Vitenskapen bak Nexalyn mannlige forsterkningstilskudd skiller dem fra andre kosttilskudd på markedet. Denne kraftige formelen kombinerer nøye utvalgte ingredienser som effektivt kan bidra til å forbedre seksuell helse og ytelse. Det kan bidra til å forbedre libido og erektil funksjon. Det kan bidra til å øke blodstrømmen til kjønnsområdet, noe som resulterer i sterkere og lengre varige ereksjoner. Det kan også øke testosteronnivået, noe som resulterer i økt energi, utholdenhet og generell sexlyst. Ved å gjenopprette hormonbalansen kan det også bidra til å forbedre humøret og redusere stress. Det kan også ha en positiv effekt på seksuell funksjon ved å hindre omdannelsen av testosteron til dihydrotestosteron (DHT), noe som kan føre til problemer som hårtap og redusert libido. Det kan bidra til å øke nivåene av fritt testosteron ved å binde seg til kjønnshormonbindende globulin (SHBG), slik at mer testosteron kan sirkulere fritt i hele kroppen. Nexalyn-piller i Australia og New Zealand kan ha som mål å gi god støtte til menn som ønsker å forbedre sin seksuelle ytelse naturlig. De aktive ingrediensene kan målrette mot ulike aspekter av seksuell helse, fra å forbedre blodstrømmen og hormonbalansen til å øke energinivået, noe som resulterer i forbedret utholdenhet, økt sensuell appetitt og mer intense orgasmer. [Klikk her for å kjøpe nå fra Nexalyns offisielle nettsted](https://ketogummies24x7.com/nexalyn-no) ##Nøkkelingredienser og deres seksuelle helsefordeler: Nøkkelingredienser spiller en viktig rolle i effektiviteten til ethvert kosttilskudd, og Nexalyn Testosterone Booster Formula er intet unntak. La oss se nærmere på noen av nøkkelingrediensene i denne kraftige formelen og hvordan de kan være til fordel for din seksuelle helse. Horny Goat Weed, også kjent som Epimedium, har blitt brukt i tradisjonell kinesisk medisin i århundrer for å forbedre libido og behandle erektil dysfunksjon. Den inneholder icariin, en forbindelse som kan bidra til å øke blodstrømmen til penis, noe som resulterer i sterkere og lengre varige ereksjoner. Tongkat Ali rotekstrakt er en annen potent ingrediens med afrodisiakumegenskaper. Det kan virke ved å øke testosteronnivået, noe som kan føre til økt utholdenhet, forbedret muskelmasse og forbedret seksuell ytelse. Sagpalmetto er assosiert med prostatahelse, men spiller også en rolle i å støtte generell seksuell velvære. Ved å hemme omdannelsen av testosteron til dihydrotestosteron (DHT), kan sagpalmetto bidra til å opprettholde sunn hormonbalanse og støtte optimal seksuell funksjon. Brenneslerotekstrakt er rik på vitamin A og C samt mineraler som jern og magnesium. Disse næringsstoffene kan støtte generell reproduktiv helse mens de øker energinivået gjennom dagen, en viktig faktor for å opprettholde intimitet med partneren din. Ved å kombinere disse kraftige naturlige ingrediensene i én formel, har Nexalyn-kapslene som mål å gi deg de nødvendige verktøyene for å realisere ditt fulle sensuelle potensial. Å legge til Nexalyn mannlige forsterkningsformel til din daglige rutine kan bidra til å forbedre både fysisk utholdenhet og mental fokus i intime øyeblikk, slik at du kan oppleve mer intens nytelse enn noen gang før! [Klikk her for å kjøpe nå fra Nexalyns offisielle nettsted](https://ketogummies24x7.com/nexalyn-no)
downloads888/MAN888	downloads888	2024-06-27T05:41:09Z	1	null	[ "aa", "ae", "ak", "am", "ab", "af", "an", "ar", "as", "av", "ay", "ba", "az", "be", "dataset:OpenGVLab/ShareGPT-4o", "dataset:ShareGPT4Video/ShareGPT4Video", "dataset:HuggingFaceFW/fineweb-edu", "dataset:HuggingFaceFW/fineweb", "license:mit", "region:us" ]	null	2024-06-27T05:37:26Z	--- license: mit datasets: - OpenGVLab/ShareGPT-4o - ShareGPT4Video/ShareGPT4Video - HuggingFaceFW/fineweb-edu - HuggingFaceFW/fineweb language: - aa - ae - ak - am - ab - af - an - ar - as - av - ay - ba - az - be metrics: - accuracy - code_eval - character ---
mohan11111/tinyllama50kjune	mohan11111	2024-06-27T05:37:51Z	0	null	[ "region:us" ]	null	2024-06-27T05:37:51Z	Entry not found
jvv7/q-FrozenLake-v1-4x4-noSlippery	jvv7	2024-06-27T05:39:08Z	0	null	[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2024-06-27T05:39:06Z	--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # Q-Learning Agent playing1 FrozenLake-v1 This is a trained model of a Q-Learning agent playing FrozenLake-v1 . ## Usage ```python model = load_from_hub(repo_id="jvv7/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
ZEGMEG/SH_WAIC_8B	ZEGMEG	2024-06-27T05:40:23Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:shenzhi-wang/Llama3-8B-Chinese-Chat", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T05:39:50Z	--- base_model: shenzhi-wang/Llama3-8B-Chinese-Chat language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - Developed by: ZEGMEG - License: apache-2.0 - Finetuned from model : shenzhi-wang/Llama3-8B-Chinese-Chat This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
munish0838/Phi-3-mini-4k-instruct-Matter-0.1-Slim-A-lora	munish0838	2024-06-27T05:42:08Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:unsloth/Phi-3-mini-4k-instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T05:41:43Z	--- 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: munish0838 - 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)
jvv7/Taxi-v3	jvv7	2024-06-27T05:41:59Z	0	null	[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2024-06-27T05:41:58Z	--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: Taxi-v3 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.56 +/- 2.71 name: mean_reward verified: false --- # Q-Learning Agent playing1 Taxi-v3 This is a trained model of a Q-Learning agent playing Taxi-v3 . ## Usage ```python model = load_from_hub(repo_id="jvv7/Taxi-v3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
quirky-lats-at-mats/wmdp_cyber_lat_4	quirky-lats-at-mats	2024-06-27T05:43:23Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T05:43:16Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
jykim310/gemva-2.6b-q4f16_1-MLC	jykim310	2024-06-27T08:50:08Z	0	null	[ "region:us" ]	null	2024-06-27T05:47:06Z	Entry not found
viyi/sd-merger_models	viyi	2024-06-27T05:50:23Z	0	null	[ "license:mit", "region:us" ]	null	2024-06-27T05:50:23Z	--- license: mit ---
richardkelly/Qwen-Qwen1.5-1.8B-1719467535	richardkelly	2024-06-27T05:52:20Z	0	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:Qwen/Qwen1.5-1.8B", "region:us" ]	null	2024-06-27T05:52:15Z	--- library_name: peft base_model: Qwen/Qwen1.5-1.8B --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### 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. 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P5ych-0/so-vits-svc-Cyberpunk2077-RU	P5ych-0	2024-06-27T06:18:03Z	0	null	[ "Cyberpunk 2077", "audio-to-audio", "ru", "region:us" ]	audio-to-audio	2024-06-27T05:52:24Z	--- language: - ru pipeline_tag: audio-to-audio tags: - Cyberpunk 2077 --- Модель голоса русской озвучки персонажа Джонни Сильверхэнд из "Cyberpunk 2077", обученный для so-vits-svc. Возможно будут и другие голоса, но очень маловероятно, хотел попробовать именно этот голос. F0 лучше в dio ставить
37channel/Llama-3-8B-Instruct-LoRA-Full-r8-alpha16-drop0.05-step5-b-loop1	37channel	2024-06-27T05:54:28Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T05:52:58Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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danelcsb/Florence-2-FT-cavity	danelcsb	2024-06-27T06:34:32Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T05:53:25Z	--- 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. 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tuskbyte/parler-tts-mini_fbdata_v1	tuskbyte	2024-06-27T09:52:19Z	0	transformers	[ "transformers", "safetensors", "vits", "text-to-audio", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	text-to-audio	2024-06-27T05:53:54Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
jacobcd52/physics-arxiv	jacobcd52	2024-06-27T05:56:04Z	0	null	[ "region:us" ]	null	2024-06-27T05:56:04Z	Entry not found
syGOAT/Mistral-v0.2-Translator-fp16	syGOAT	2024-06-27T05:59:54Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-27T05:56:06Z	Entry not found
jvv7/q-FrozenLake-v1-8x8-Slippery	jvv7	2024-06-27T05:56:49Z	0	null	[ "region:us" ]	null	2024-06-27T05:56:49Z	Entry not found
Dread-Fox/DreadFox	Dread-Fox	2024-06-27T06:02:21Z	0	null	[ "license:cc-by-nc-4.0", "region:us" ]	null	2024-06-27T06:02:21Z	--- license: cc-by-nc-4.0 ---
monkeysandy/ddpm-butterflies-128	monkeysandy	2024-06-27T06:02:41Z	0	null	[ "region:us" ]	null	2024-06-27T06:02:41Z	Entry not found
thaisonatk/envit5-base-iwslt15	thaisonatk	2024-06-27T17:35:36Z	0	transformers	[ "transformers", "tensorboard", "safetensors", "mt5", "text2text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2024-06-27T06:03:27Z	Entry not found
geraldabrhm/llama-3-8b-regular-simplecontext-32lora-lr8_5-8batch	geraldabrhm	2024-06-27T12:25:05Z	0	null	[ "safetensors", "region:us" ]	null	2024-06-27T06:03:40Z	Entry not found
JefiRyan/gemma-gguf	JefiRyan	2024-06-27T06:12:29Z	0	null	[ "region:us" ]	null	2024-06-27T06:04:02Z	Entry not found
buianh0803/YOLOv10_Finetune_Helmet_Safety	buianh0803	2024-06-27T06:05:29Z	0	null	[ "region:us" ]	null	2024-06-27T06:05:29Z	Entry not found
atanu2531/smallpython	atanu2531	2024-06-27T06:07:40Z	0	null	[ "license:gpl-3.0", "region:us" ]	null	2024-06-27T06:07:39Z	--- license: gpl-3.0 ---
ridhoo/resyep	ridhoo	2024-06-27T06:15:14Z	0	null	[ "region:us" ]	null	2024-06-27T06:09:02Z	Entry not found
BigHuggyD/alpindale_magnum-72b-v1_exl2_4.0bpw_h8	BigHuggyD	2024-06-27T06:26:31Z	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "chat", "conversational", "en", "zh", "license:other", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "4-bit", "exl2", "region:us" ]	text-generation	2024-06-27T06:09:15Z	--- license: other license_name: tongyi-qianwen license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE language: - en - zh pipeline_tag: text-generation tags: - chat --- ![](https://files.catbox.moe/ngqnb1.png) This is the first in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of [Qwen-2 72B Instruct](https://huggingface.co/Qwen/Qwen2-72B-Instruct). ## Prompting Model has been Instruct tuned with the ChatML formatting. A typical input would look like this: ```py """<\|im_start\|>user Hi there!<\|im_end\|> <\|im_start\|>assistant Nice to meet you!<\|im_end\|> <\|im_start\|>user Can I ask a question?<\|im_end\|> <\|im_start\|>assistant """ ``` ## Credits This model has been a team effort, credits go to: - [Sao10K](https://huggingface.co/Sao10K) for help with (and cleaning up!) the dataset. - [alpindale](https://huggingface.co/alpindale) for the training. - [kalomaze](https://huggingface.co/kalomaze) for helping with the hyperparameter tuning. - Various other people for their continued help as we tuned the parameters, restarted failed runs. In no particular order: [Doctor Shotgun](https://huggingface.co/Doctor-Shotgun), [Lucy](https://huggingface.co/lucyknada), [Nopm](https://huggingface.co/nopm), [Mango](https://huggingface.co/MangoMango69420), and the rest of the Silly Tilly. And last but not least, we'd like to thank [Kearm](https://twitter.com/Nottlespike) for sponsoring the compute needed to train this model. ## Training The training was done with 55 million tokens of high-quality RP data, over 1.5 epochs. We used 8x [AMD Instinct™ MI300X Accelerators](https://www.amd.com/en/products/accelerators/instinct/mi300/mi300x.html) for the full-parameter fine-tuning of the model. [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) ## Safety ...
gaur3009/Rook-us	gaur3009	2024-06-27T06:20:34Z	0	null	[ "license:unknown", "region:us" ]	null	2024-06-27T06:16:56Z	--- license: unknown ---
starnet/16-star21-06-27	starnet	2024-06-27T06:26:38Z	0	null	[ "any-to-any", "omega", "omegalabs", "bittensor", "agi", "license:mit", "region:us" ]	null	2024-06-27T06:19:36Z	--- license: mit tags: - any-to-any - omega - omegalabs - bittensor - agi --- This is an Any-to-Any model checkpoint for the OMEGA Labs x Bittensor Any-to-Any subnet. Check out the [git repo](https://github.com/omegalabsinc/omegalabs-anytoany-bittensor) and find OMEGA on X: [@omegalabsai](https://x.com/omegalabsai).
akash-43/murad-translator	akash-43	2024-06-27T06:20:31Z	0	null	[ "license:mit", "region:us" ]	null	2024-06-27T06:20:31Z	--- license: mit ---
37channel/Llama-3-8B-Instruct-LoRA-Full-r8-alpha16-drop0.05-step6-a-loop1	37channel	2024-06-27T06:24:15Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T06:22:48Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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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]
rakib72642/PepsodentCore	rakib72642	2024-06-27T06:24:36Z	0	null	[ "region:us" ]	null	2024-06-27T06:22:51Z	Entry not found
twodigit/Mistral-7B-Instruct-v0.3-kowiki_categories-sft-lora-4096-lr1e-5-e1-b4	twodigit	2024-06-27T06:23:31Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T06:23:21Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
ningxingg/sic	ningxingg	2024-06-27T06:49:41Z	0	null	[ "region:us" ]	null	2024-06-27T06:24:12Z	Entry not found
Gille/BiggerWizardLM-2-7B-Extended-GGUF	Gille	2024-06-27T07:09:53Z	0	null	[ "region:us" ]	null	2024-06-27T06:25:06Z	Entry not found
victimhacker/experiment1	victimhacker	2024-06-27T06:26:48Z	0	null	[ "region:us" ]	null	2024-06-27T06:25:58Z	Entry not found
twodigit/Qwen2-7B-Instruct-kowiki_categories-sft-lora-4096-lr1e-5-e1-b4	twodigit	2024-06-27T06:26:22Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T06:26:11Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### 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]
Yamadronxzf/Hol	Yamadronxzf	2024-06-27T06:26:25Z	0	null	[ "license:openrail", "region:us" ]	null	2024-06-27T06:26:25Z	--- license: openrail ---
Gatsu0728/G-test	Gatsu0728	2024-06-27T08:07:19Z	0	null	[ "region:us" ]	null	2024-06-27T06:27:30Z	Entry not found
brianfeng/summ	brianfeng	2024-06-27T06:28:24Z	0	null	[ "region:us" ]	null	2024-06-27T06:28:24Z	Entry not found
twodigit/Meta-Llama-3-8B-Instruct-kowiki_categories-sft-lora-4096-lr1e-5-e1-b4	twodigit	2024-06-27T06:28:59Z	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-27T06:28:48Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- 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]
seohyunqkr/MUsE	seohyunqkr	2024-06-27T06:53:43Z	0	null	[ "safetensors", "license:mit", "region:us" ]	null	2024-06-27T06:30:50Z	--- license: mit ---
Almancy/finetuning-emotion-model-5-v3	Almancy	2024-06-27T08:44:40Z	0	transformers	[ "transformers", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-06-27T06:32:53Z	--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: finetuning-emotion-model-5-v3 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. --> # finetuning-emotion-model-5-v3 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9127 - Accuracy: 0.6077 - F1: 0.6056 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| F1 \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:------:\| \| 0.949 \| 1.0 \| 2500 \| 0.9358 \| 0.5976 \| 0.5977 \| \| 0.8216 \| 2.0 \| 5000 \| 0.9127 \| 0.6077 \| 0.6056 \| ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1
sarpba/llama-3-8b-Instruct-hun	sarpba	2024-07-01T18:11:26Z	0	null	[ "tensorboard", "region:us" ]	null	2024-06-27T06:34:09Z	Entry not found
kaizhu1125/test	kaizhu1125	2024-06-27T06:35:06Z	0	null	[ "region:us" ]	null	2024-06-27T06:35:06Z	Entry not found
KN123/nl2-task-csv.ipynb	KN123	2024-06-27T06:37:02Z	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "mistral", "trl", "en", "base_model:unsloth/mistral-7b-v0.3-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-06-27T06:36:51Z	--- base_model: unsloth/mistral-7b-v0.3-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - Developed by: KN123 - License: apache-2.0 - Finetuned from model : unsloth/mistral-7b-v0.3-bnb-4bit This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

Granther/phi3-fine-tuning-files

Granther

2024-06-27T03:54:09Z

0

null

[ "region:us" ]

null

2024-06-27T03:50:30Z

Entry not found

tstars/alpaca_lora

tstars

2024-06-27T03:50:40Z

0

null

[ "region:us" ]

null

2024-06-27T03:50:40Z

Entry not found

habulaj/1097311636

habulaj

2024-06-27T03:51:10Z

0

null

[ "region:us" ]

null

2024-06-27T03:51:05Z

Entry not found

danielhenel/smishing-detection-mistral-7b-instruct-v0.3

danielhenel

2024-06-27T03:53:51Z

0

transformers

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

null

2024-06-27T03:53:09Z

--- 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]

habulaj/522734496225

habulaj

2024-06-27T03:54:11Z

0

null

[ "region:us" ]

null

2024-06-27T03:54:08Z

Entry not found

Ksgk-fy/phillipine_customer_ooc_patch_v4.0_Maria_ooc_patch_v1

Ksgk-fy

2024-07-01T06:53:16Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-27T03:57:28Z

Entry not found

ayousanz/Style-Bert-VITS2-jp_extra_large

ayousanz

2024-06-27T04:02:34Z

0

7

null

[ "region:us" ]

null

2024-06-27T04:00:50Z

Style-Bert-VITS2用事前学習モデルjp_extra_large_Ver20240627_20240630 ====許可している内容==== １：githubやhuggingface等の不特定多数がダウンロード可能なサイトへのアップロード（転載）２：この事前学習モデルは俺 or 私が作った！という自作発言及び、自身の成果物としての宣伝・配布・販売３：禁止事項の改変やライセンスの変更（自作発言をする場合は自由に変更して構わない） ====禁止事項==== １：転載時に転載元を記載しない。＊悪意あるサイトへの誘導を防ぐ為。２：転載時に転載元のアップロード者及び開発者に関する内容を記載しない。＊転載しただけの人が開発者と混同されないようにするため。＊＊自作発言をした人が出てきた場合に混沌とするため。 ====使用上の注意==== 使用可能な記号として:　;　=　#　<　>　^　(　)　*の計10個を追加しています。追加学習に用いるデータが多い場合に差が出やすいです。 VRAM16GB以上の環境で学習をするのを想定しています。 G_XXXXX.pthのサイズは約1.4GB XXXX_eYYY_sZZZZZZ.safetensorsのサイズは約400MB ====使い方==== 各フォルダーに上書き。

Pingkkkkklksl/my-pretrained-model

Pingkkkkklksl

2024-06-27T04:01:16Z

0

null

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

null

2024-06-27T04:01:16Z

--- license: mit ---

nachus2/modeltest

nachus2

2024-06-27T04:03:32Z

0

asteroid

[ "asteroid", "biology", "chemistry", "climate", "audio-classification", "ar", "license:artistic-2.0", "region:us" ]

audio-classification

2024-06-27T04:01:57Z

--- license: artistic-2.0 language: - ar metrics: - accuracy - bleu - character library_name: asteroid pipeline_tag: audio-classification tags: - biology - chemistry - climate ---

ariG23498/zephyr-7b-gemma-v0.1

ariG23498

2024-06-27T04:04:14Z

0

null

[ "region:us" ]

null

2024-06-27T04:04:14Z

Entry not found

TioPanda/pandev-blocks-v4

TioPanda

2024-06-27T04:07:33Z

0

transformers

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

null

2024-06-27T04:06:56Z

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

smokewulf/Devika

smokewulf

2024-06-27T04:07:47Z

0

null

[ "region:us" ]

null

2024-06-27T04:07:47Z

Entry not found

geraldabrhm/llama-3-8b-regular-simplecontext-32lora-lr8_5-32batch

geraldabrhm

2024-06-27T05:57:03Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-27T04:08:47Z

Entry not found

EmersonKaleb/chatbot

EmersonKaleb

2024-06-27T04:09:19Z

0

null

[ "region:us" ]

null

2024-06-27T04:09:18Z

Entry not found

Litzy619/MIS0626T4F200200

Litzy619

2024-06-27T10:38:51Z

0

null

[ "region:us" ]

null

2024-06-27T04:11:04Z

Entry not found

vedkulkarni/whisper-base-hi

vedkulkarni

2024-06-27T04:20:43Z

0

null

[ "region:us" ]

null

2024-06-27T04:20:43Z

Entry not found

Haary/USK_Mistral_7B_Unsloth

Haary

2024-06-27T05:12:41Z

0

transformers

[ "transformers", "safetensors", "text-generation-inference", "unsloth", "mistral", "trl", "en", "id", "dataset:Haary/QA_USK_dataset", "base_model:Ichsan2895/Merak-7B-v4", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

2024-06-27T04:23:37Z

--- base_model: Ichsan2895/Merak-7B-v4 language: - en - id license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl datasets: - Haary/QA_USK_dataset --- # Uploaded model - **Developed by:** Haary - **License:** apache-2.0 - **Finetuned from Indonesia model :** [Ichsan2895/Merak-7B-v4](https://huggingface.co/Ichsan2895/Merak-7B-v4) - **Base model :** [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

PhillipGuo/hp-lat-llama-No_PCA-epsilon3.0-pgd_layer12-def_layer13_14_15-wikitext-fullrank-97

PhillipGuo

2024-06-27T04:24:06Z

0

null

[ "region:us" ]

null

2024-06-27T04:24:06Z

Entry not found

Azaz666/mt5-small-finetuned-CEP

Azaz666

2024-06-27T04:25:13Z

0

null

[ "region:us" ]

null

2024-06-27T04:25:13Z

Entry not found

PhillipGuo/hp-lat-llama-No_PCA-epsilon0.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-99

PhillipGuo

2024-06-27T04:26:02Z

0

null

[ "region:us" ]

null

2024-06-27T04:26:02Z

Entry not found

starnet/15-star21-06-27

starnet

2024-06-27T04:34:12Z

0

null

[ "any-to-any", "omega", "omegalabs", "bittensor", "agi", "license:mit", "region:us" ]

null

2024-06-27T04:26:54Z

--- license: mit tags: - any-to-any - omega - omegalabs - bittensor - agi --- This is an Any-to-Any model checkpoint for the OMEGA Labs x Bittensor Any-to-Any subnet. Check out the [git repo](https://github.com/omegalabsinc/omegalabs-anytoany-bittensor) and find OMEGA on X: [@omegalabsai](https://x.com/omegalabsai).

camenduru/MeshAnything

camenduru

2024-06-27T04:29:21Z

0

null

[ "region:us" ]

null

2024-06-27T04:28:08Z

Entry not found

PhillipGuo/hp-lat-llama-No_PCA-epsilon1.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-100

PhillipGuo

2024-06-27T04:30:14Z

0

null

[ "region:us" ]

null

2024-06-27T04:30:14Z

Entry not found

PhillipGuo/hp-lat-llama-No_PCA-epsilon0.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-100

PhillipGuo

2024-06-27T04:31:26Z

0

null

[ "region:us" ]

null

2024-06-27T04:31:26Z

Entry not found

PhillipGuo/hp-lat-llama-No_PCA-epsilon3.0-pgd_layer12-def_layer13_14_15-wikitext-fullrank-100

PhillipGuo

2024-06-27T04:32:33Z

0

null

[ "region:us" ]

null

2024-06-27T04:32:32Z

Entry not found

PhillipGuo/hp-lat-llama-No_PCA-epsilon0.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-96

PhillipGuo

2024-06-27T04:33:51Z

0

null

[ "region:us" ]

null

2024-06-27T04:33:51Z

Entry not found

eoinf/unlearning_saes

eoinf

2024-06-27T06:55:05Z

0

null

[ "region:us" ]

null

2024-06-27T04:34:23Z

Entry not found

GrowingApple/llama-3-8B-medical-kor-chat_test

GrowingApple

2024-06-27T04:43:52Z

0

transformers

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

null

2024-06-27T04:35:17Z

--- 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]

PhillipGuo/hp-lat-llama-No_PCA-epsilon1.5-pgd_layer12-def_layer13_14_15-wikitext-fullrank-99

PhillipGuo

2024-06-27T04:37:30Z

0

null

[ "region:us" ]

null

2024-06-27T04:37:30Z

Entry not found

GraydientPlatformAPI/loras-jun27b

GraydientPlatformAPI

2024-06-27T04:43:04Z

0

null

[ "region:us" ]

null

2024-06-27T04:38:43Z

Entry not found

nan7892/Yinan_test_ppo_7b

nan7892

2024-06-27T04:40:45Z

0

1

null

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

null

2024-06-27T04:40:45Z

--- license: apache-2.0 ---

Azaz666/t5-base-finetuned-CEP

Azaz666

2024-06-27T04:42:10Z

0

null

[ "region:us" ]

null

2024-06-27T04:42:10Z

Entry not found

valerielucro/mistral_gsm8k_beta_0.4_epoch3

valerielucro

2024-06-27T04:52:08Z

0

transformers

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

null

2024-06-27T04:51:48Z

--- 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]

Surekel/training

Surekel

2024-06-27T05:04:36Z

0

null

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

null

2024-06-27T04:52:02Z

--- license: mit ---

foduucom/resume-extractor

foduucom

2024-06-27T05:19:58Z

0

null

[ "resume", "extractor", "resume extractor", "pdf", "extract", "cv parser", "pdf extraction", "document analysis", "unstructured document", "DataProcessing", "TextToJSON", "resume parser", "resume information extractor", "resume data extraction", "en", "region:us" ]

null

2024-06-27T04:54:51Z

--- language: - en tags: - resume - extractor - resume extractor - pdf - extract - cv parser - pdf extraction - document analysis - unstructured document - DataProcessing - TextToJSON - resume parser - resume information extractor - resume data extraction --- # PDF Resume Information Extractor ## Description This Python script extracts information from PDF resumes and converts it into a structured JSON format using the Ollama language model. It's designed to automate the process of parsing resumes and extracting key details, making it easier for HR departments, recruiters, and organizations to process large volumes of applications efficiently. What sets this script apart is its ability to handle various resume formats and styles. It uses a predefined JSON template to ensure consistent output structure, making it easier to integrate with other systems or databases. The script is designed to be flexible, allowing for customization of the output format and the underlying language model. We invite you to explore the potential of this script and its data extraction capabilities. For those interested in harnessing its power or seeking further collaboration, we encourage you to reach out to us or contribute to the project on GitHub. Your input drives our continuous improvement, as we collectively pave the way towards enhanced data extraction and document analysis. - **Developed by:** FODUU AI - **Model type:** Extraction - **Task:** Resume Parsing and Information Extraction ### Supported Output Fields The exact fields depend on the JSON template which have includes the following fields: ['name', 'email', 'phone_1', 'phone_2', 'address', 'city', 'highest_education', 'is_fresher','is_student', 'professional_experience_in_years', 'skills' ,'linkedin' , 'applied_for_profile', 'education', 'professional_experience'] ## Uses ### Direct Use The Resume Information Extractor can be directly used for parsing resume PDFs and extracting structured information. It's particularly useful for HR departments, recruitment agencies, or any organization that deals with large volumes of resumes. ### Downstream Use The extracted information can be used for various downstream tasks such as candidate matching, resume scoring, or populating applicant tracking systems. ### Out-of-Scope Use The model is not designed for tasks unrelated to resume parsing or for processing documents that are not resumes. ## Risks, and Limitations The Resume Information Extractor may have some limitations and risks, including: - Performance may vary based on the format and structure of the input resume. - The quality of extraction depends on the capabilities of the underlying Ollama model. - It may struggle with highly unconventional resume formats or non-English resumes. - The script does not verify the accuracy of the information in the resume. ### Recommendations Users should be aware of the script's limitations and potential risks. It's recommended to manually verify the extracted information for critical applications. Further testing and validation are advised for specific use cases to evaluate its performance accurately. ## How to Get Started with the Model To begin using the Resume Information Extractor, follow these steps: 1. Clone this repository: ```bash git clone https://huggingface.co/nehulagrawal/resume-extractor ``` 2. Install the required packages: ```bash pip install langchain_community pdfminer.six ollama ``` or ```bash pip install -r requirements.txt ``` 3. Ensure you have Ollama set up and running with the "llama3" model. 4. Use this Python script: ```python from pdfminer.high_level import extract_text from json_helper import InputData as input def extract_text_from_pdf(pdf_path): return extract_text(pdf_path) text = extract_text_from_pdf(r'path/to/your/document/pdf') llm = input.llm() data = llm.invoke(input.input_data(text)) print(data) ``` ## Objective This script uses the Ollama language model to understand and extract information from resume text. The specific architecture depends on the Ollama model being used. ## Contact For inquiries and contributions, please contact us at [email protected]. ```bibtex @contact{foduu, author = {Foduu}, title = {Resume Extractor}, year = {2024} } ```

tomreichel/proof-repair-model

tomreichel

2024-06-27T04:55:36Z

0

transformers

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

null

2024-06-27T04:55:24Z

--- 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]

tomreichel/proof-synthesis-model

tomreichel

2024-06-27T04:57:01Z

0

transformers

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

null

2024-06-27T04:56:50Z

--- 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]

pig142857/cobra_mambaV2

pig142857

2024-07-02T03:08:35Z

0

null

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

null

2024-06-27T04:58:39Z

--- license: mit ---

DZERV/lonzodontknowgng

DZERV

2024-06-27T05:01:37Z

0

null

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

null

2024-06-27T05:00:24Z

--- license: openrail ---

Keerthan40/Driver_Alert_System

Keerthan40

2024-06-27T06:27:24Z

0

transformers

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

null

2024-06-27T05:02:47Z

--- 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]

lfnothing/code-search-net-tokenizer

lfnothing

2024-06-27T05:08:39Z

0

transformers

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

null

2024-06-27T05:08:38Z

--- 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]

shannu999/hv

shannu999

2024-06-27T05:11:08Z

0

null

[ "region:us" ]

null

2024-06-27T05:11:08Z

Entry not found

haerxiluo/my-cv-boneage

haerxiluo

2024-06-27T05:45:39Z

0

null

[ "region:us" ]

null

2024-06-27T05:12:09Z

Entry not found

BigMitchell/puff_yfm

BigMitchell

2024-06-27T05:49:40Z

0

null

[ "region:us" ]

null

2024-06-27T05:14:21Z

Entry not found

firsthac/unauth

firsthac

2024-06-27T05:15:36Z

0

null

[ "region:us" ]

null

2024-06-27T05:15:36Z

Entry not found

alxcarln/esm2_t30_150M_UR50D-finetuned-localization

alxcarln

2024-06-27T05:16:38Z

0

null

[ "region:us" ]

null

2024-06-27T05:16:38Z

Entry not found

firsthac/unauth1

firsthac

2024-06-27T05:16:41Z

0

null

[ "region:us" ]

null

2024-06-27T05:16:41Z

Entry not found

alxcarln/esm2_t6_8M_UR50D-finetuned-localization

alxcarln

2024-06-27T05:20:37Z

0

null

[ "region:us" ]

null

2024-06-27T05:20:36Z

Entry not found

KhanLee0930/q-FrozenLake-v1-4x4-noSlippery

KhanLee0930

2024-06-27T05:21:45Z

0

null

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

reinforcement-learning

2024-06-27T05:21:43Z

--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **FrozenLake-v1** This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** . ## Usage ```python model = load_from_hub(repo_id="KhanLee0930/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```

KhanLee0930/Taxi-v3

KhanLee0930

2024-06-27T05:22:36Z

0

null

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

reinforcement-learning

2024-06-27T05:22:34Z

--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: Taxi-v3 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.54 +/- 2.73 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **Taxi-v3** This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . ## Usage ```python model = load_from_hub(repo_id="KhanLee0930/Taxi-v3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```

Bodo121/Bodosa121

Bodo121

2024-06-27T05:30:16Z

0

null

[ "region:us" ]

null

2024-06-27T05:30:16Z

Entry not found

VKapseln475/Nexalyn41422

VKapseln475

2024-06-27T05:38:19Z

0

null

[ "region:us" ]

null

2024-06-27T05:31:53Z

# [NY] Nexalyn Danmark Erfaringer - Nexalyn Anmeldelser Dosis og Virker Officiel pris, køb [NY] Nexalyn Danmark Erfaringer At forbrænde fedt i besværlige områder er en udfordring for mange mennesker på deres vægttabsrejse. Dette stædige kropsfedt kan være frustrerende og svært at målrette mod med kost og motion alene. Nexaslim-tillægget kan dog give den løsning, du har ledt efter. ## **[Klik her for at købe nu fra Nexalyn officielle hjemmeside](https://capsules24x7.com/nexalyn-danmark)** ## Hvordan hjælper dette produkt dig med at øge dit energiniveau? Hvis du mangler energi og udholdenhed, kan Nexalyn testo booster-kapsler i Sydafrika være den løsning, du har ledt efter. Dette kraftfulde kosttilskud har ingredienser, der kan hjælpe med at booste energiniveauet og revitalisere din krop. Det kan virke ved at øge testosteronniveauet, hvilket kan føre til forbedret energi og vitalitet. Det kan også virke ved at forbedre libido og seksuel ydeevne. Produktet indeholder forbindelser, der kan øge produktionen af nitrogenoxid, som kan være med til at forbedre blodgennemstrømningen i hele kroppen, herunder til musklerne. Denne forbedrede cirkulation kan føre til øget energiniveau. Det kan understøtte hormonbalancen, samtidig med at det giver en naturlig kilde til antioxidanter, der kan fremme det generelle velvære. Nexalyn testosteron booster spiller en vigtig rolle i at understøtte sunde hormonniveauer i kroppen, samt fremme sund prostatafunktion, som begge kan bidrage til øget energiniveau. Ved at tilføje dette produkt til din daglige rutine, kan du opleve en mærkbar forbedring i dit overordnede energiniveau i løbet af dagen. Uanset om det er at håndtere opgaver på arbejdet eller nyde intime stunder med din partner, kan dette tillæg give dig det ekstra boost, du har brug for for at komme igennem. ## Hvordan forbedrer dette supplement din sensuelle ydeevne? Når det kommer til at forbedre din sensuelle ydeevne, er Nexalyn mandlig forbedring her for at hjælpe dig. Dette kraftfulde supplement kan øge din seksuelle energi og udholdenhed, så du kan få mere intense og tilfredsstillende oplevelser i soveværelset. ## **[Klik her for at købe nu fra Nexalyn officielle hjemmeside](https://capsules24x7.com/nexalyn-danmark)**

JefiRyan/llama-3-8b-gguf

JefiRyan

2024-06-27T05:34:49Z

0

null

[ "region:us" ]

null

2024-06-27T05:32:04Z

Entry not found

tuskbyte/raw_nld_v5_char_1

tuskbyte

2024-06-27T05:32:39Z

0

transformers

[ "transformers", "safetensors", "vits", "text-to-audio", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

text-to-audio

2024-06-27T05:32:29Z

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

ShapeKapseln33/Nexalyn23

ShapeKapseln33

2024-06-27T05:39:53Z

0

null

[ "region:us" ]

null

2024-06-27T05:35:12Z

[Offisiell] Nexalyn Anmeldelser: I en verden hvor vitalitet og ytelse ofte er synonymt med suksess, er det viktig å opprettholde topp fysisk form. For menn strekker dette seg ofte utover bare kondisjon til områder med vitalitet, virilitet og generelt velvære. Men ettersom alderen innhenter oss, kan ulike faktorer hemme vår evne til å opprettholde optimal ytelse og tilfredshet i disse rikene. **[Klikk her for å kjøpe nå fra Nexalyns offisielle nettsted](https://ketogummies24x7.com/nexalyn-no)** ##Introduksjon til Nexalyn Vil du ta dine seksuelle opplevelser til neste nivå? Hvis ja, se ikke lenger enn Nexalyn Testosterone Booster Formula, det revolusjonerende kosttilskuddet som skaper bølger i verden av seksuell helse. Hvis du noen gang har ønsket deg sterkere ereksjoner, økt sensuell appetitt og eksplosive orgasmer, så har du kommet til rett sted. I dag skal vi diskutere alt du trenger å vite om Nexalyn mannlige forsterkningstilskudd, fra den vitenskapelig støttede formelen til nøkkelingrediensene som vil hjelpe deg å øke din seksuelle ytelse. ##Vitenskapen bak Nexalyn Testo booster og hvordan den fungerer: Vitenskapen bak Nexalyn mannlige forsterkningstilskudd skiller dem fra andre kosttilskudd på markedet. Denne kraftige formelen kombinerer nøye utvalgte ingredienser som effektivt kan bidra til å forbedre seksuell helse og ytelse. Det kan bidra til å forbedre libido og erektil funksjon. Det kan bidra til å øke blodstrømmen til kjønnsområdet, noe som resulterer i sterkere og lengre varige ereksjoner. Det kan også øke testosteronnivået, noe som resulterer i økt energi, utholdenhet og generell sexlyst. Ved å gjenopprette hormonbalansen kan det også bidra til å forbedre humøret og redusere stress. Det kan også ha en positiv effekt på seksuell funksjon ved å hindre omdannelsen av testosteron til dihydrotestosteron (DHT), noe som kan føre til problemer som hårtap og redusert libido. Det kan bidra til å øke nivåene av fritt testosteron ved å binde seg til kjønnshormonbindende globulin (SHBG), slik at mer testosteron kan sirkulere fritt i hele kroppen. Nexalyn-piller i Australia og New Zealand kan ha som mål å gi god støtte til menn som ønsker å forbedre sin seksuelle ytelse naturlig. De aktive ingrediensene kan målrette mot ulike aspekter av seksuell helse, fra å forbedre blodstrømmen og hormonbalansen til å øke energinivået, noe som resulterer i forbedret utholdenhet, økt sensuell appetitt og mer intense orgasmer. **[Klikk her for å kjøpe nå fra Nexalyns offisielle nettsted](https://ketogummies24x7.com/nexalyn-no)** ##Nøkkelingredienser og deres seksuelle helsefordeler: Nøkkelingredienser spiller en viktig rolle i effektiviteten til ethvert kosttilskudd, og Nexalyn Testosterone Booster Formula er intet unntak. La oss se nærmere på noen av nøkkelingrediensene i denne kraftige formelen og hvordan de kan være til fordel for din seksuelle helse. Horny Goat Weed, også kjent som Epimedium, har blitt brukt i tradisjonell kinesisk medisin i århundrer for å forbedre libido og behandle erektil dysfunksjon. Den inneholder icariin, en forbindelse som kan bidra til å øke blodstrømmen til penis, noe som resulterer i sterkere og lengre varige ereksjoner. Tongkat Ali rotekstrakt er en annen potent ingrediens med afrodisiakumegenskaper. Det kan virke ved å øke testosteronnivået, noe som kan føre til økt utholdenhet, forbedret muskelmasse og forbedret seksuell ytelse. Sagpalmetto er assosiert med prostatahelse, men spiller også en rolle i å støtte generell seksuell velvære. Ved å hemme omdannelsen av testosteron til dihydrotestosteron (DHT), kan sagpalmetto bidra til å opprettholde sunn hormonbalanse og støtte optimal seksuell funksjon. Brenneslerotekstrakt er rik på vitamin A og C samt mineraler som jern og magnesium. Disse næringsstoffene kan støtte generell reproduktiv helse mens de øker energinivået gjennom dagen, en viktig faktor for å opprettholde intimitet med partneren din. Ved å kombinere disse kraftige naturlige ingrediensene i én formel, har Nexalyn-kapslene som mål å gi deg de nødvendige verktøyene for å realisere ditt fulle sensuelle potensial. Å legge til Nexalyn mannlige forsterkningsformel til din daglige rutine kan bidra til å forbedre både fysisk utholdenhet og mental fokus i intime øyeblikk, slik at du kan oppleve mer intens nytelse enn noen gang før! **[Klikk her for å kjøpe nå fra Nexalyns offisielle nettsted](https://ketogummies24x7.com/nexalyn-no)**

downloads888/MAN888

downloads888

2024-06-27T05:41:09Z

0

1

null

[ "aa", "ae", "ak", "am", "ab", "af", "an", "ar", "as", "av", "ay", "ba", "az", "be", "dataset:OpenGVLab/ShareGPT-4o", "dataset:ShareGPT4Video/ShareGPT4Video", "dataset:HuggingFaceFW/fineweb-edu", "dataset:HuggingFaceFW/fineweb", "license:mit", "region:us" ]

null

2024-06-27T05:37:26Z

--- license: mit datasets: - OpenGVLab/ShareGPT-4o - ShareGPT4Video/ShareGPT4Video - HuggingFaceFW/fineweb-edu - HuggingFaceFW/fineweb language: - aa - ae - ak - am - ab - af - an - ar - as - av - ay - ba - az - be metrics: - accuracy - code_eval - character ---

mohan11111/tinyllama50kjune

mohan11111

2024-06-27T05:37:51Z

0

null

[ "region:us" ]

null

2024-06-27T05:37:51Z

Entry not found

jvv7/q-FrozenLake-v1-4x4-noSlippery

jvv7

2024-06-27T05:39:08Z

0

null

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

reinforcement-learning

2024-06-27T05:39:06Z

--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **FrozenLake-v1** This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** . ## Usage ```python model = load_from_hub(repo_id="jvv7/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```

ZEGMEG/SH_WAIC_8B

ZEGMEG

2024-06-27T05:40:23Z

0

transformers

[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:shenzhi-wang/Llama3-8B-Chinese-Chat", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

2024-06-27T05:39:50Z

--- base_model: shenzhi-wang/Llama3-8B-Chinese-Chat language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - **Developed by:** ZEGMEG - **License:** apache-2.0 - **Finetuned from model :** shenzhi-wang/Llama3-8B-Chinese-Chat This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

munish0838/Phi-3-mini-4k-instruct-Matter-0.1-Slim-A-lora

munish0838

2024-06-27T05:42:08Z

0

transformers

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

null

2024-06-27T05:41:43Z

--- 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:** munish0838 - **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)

jvv7/Taxi-v3

jvv7

2024-06-27T05:41:59Z

0

null

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

reinforcement-learning

2024-06-27T05:41:58Z

--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: Taxi-v3 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.56 +/- 2.71 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **Taxi-v3** This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . ## Usage ```python model = load_from_hub(repo_id="jvv7/Taxi-v3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```

quirky-lats-at-mats/wmdp_cyber_lat_4

quirky-lats-at-mats

2024-06-27T05:43:23Z

0

transformers

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

null

2024-06-27T05:43:16Z

--- 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]

jykim310/gemva-2.6b-q4f16_1-MLC

jykim310

2024-06-27T08:50:08Z

0

null

[ "region:us" ]

null

2024-06-27T05:47:06Z

Entry not found

viyi/sd-merger_models

viyi

2024-06-27T05:50:23Z

0

null

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

null

2024-06-27T05:50:23Z

--- license: mit ---

richardkelly/Qwen-Qwen1.5-1.8B-1719467535

richardkelly

2024-06-27T05:52:20Z

0

peft

[ "peft", "safetensors", "arxiv:1910.09700", "base_model:Qwen/Qwen1.5-1.8B", "region:us" ]

null

2024-06-27T05:52:15Z

--- library_name: peft base_model: Qwen/Qwen1.5-1.8B --- # Model Card for Model ID  ## Model Details ### Model Description  - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.11.1

P5ych-0/so-vits-svc-Cyberpunk2077-RU

P5ych-0

2024-06-27T06:18:03Z

0

null

[ "Cyberpunk 2077", "audio-to-audio", "ru", "region:us" ]

audio-to-audio

2024-06-27T05:52:24Z

--- language: - ru pipeline_tag: audio-to-audio tags: - Cyberpunk 2077 --- Модель голоса русской озвучки персонажа Джонни Сильверхэнд из "Cyberpunk 2077", обученный для so-vits-svc. Возможно будут и другие голоса, но очень маловероятно, хотел попробовать именно этот голос. F0 лучше в dio ставить

37channel/Llama-3-8B-Instruct-LoRA-Full-r8-alpha16-drop0.05-step5-b-loop1

37channel

2024-06-27T05:54:28Z

0

transformers

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

null

2024-06-27T05:52:58Z

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

danelcsb/Florence-2-FT-cavity

danelcsb

2024-06-27T06:34:32Z

0

transformers

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

null

2024-06-27T05:53:25Z

--- 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]

tuskbyte/parler-tts-mini_fbdata_v1

tuskbyte

2024-06-27T09:52:19Z

0

transformers

[ "transformers", "safetensors", "vits", "text-to-audio", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

text-to-audio

2024-06-27T05:53:54Z

--- 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]

jacobcd52/physics-arxiv

jacobcd52

2024-06-27T05:56:04Z

0

null

[ "region:us" ]

null

2024-06-27T05:56:04Z

Entry not found

syGOAT/Mistral-v0.2-Translator-fp16

syGOAT

2024-06-27T05:59:54Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-27T05:56:06Z

Entry not found

jvv7/q-FrozenLake-v1-8x8-Slippery

jvv7

2024-06-27T05:56:49Z

0

null

[ "region:us" ]

null

2024-06-27T05:56:49Z

Entry not found

Dread-Fox/DreadFox

Dread-Fox

2024-06-27T06:02:21Z

0

null

[ "license:cc-by-nc-4.0", "region:us" ]

null

2024-06-27T06:02:21Z

--- license: cc-by-nc-4.0 ---

monkeysandy/ddpm-butterflies-128

monkeysandy

2024-06-27T06:02:41Z

0

null

[ "region:us" ]

null

2024-06-27T06:02:41Z

Entry not found

thaisonatk/envit5-base-iwslt15

thaisonatk

2024-06-27T17:35:36Z

0

transformers

[ "transformers", "tensorboard", "safetensors", "mt5", "text2text-generation", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text2text-generation

2024-06-27T06:03:27Z

Entry not found

geraldabrhm/llama-3-8b-regular-simplecontext-32lora-lr8_5-8batch

geraldabrhm

2024-06-27T12:25:05Z

0

null

[ "safetensors", "region:us" ]

null

2024-06-27T06:03:40Z

Entry not found

JefiRyan/gemma-gguf

JefiRyan

2024-06-27T06:12:29Z

0

null

[ "region:us" ]

null

2024-06-27T06:04:02Z

Entry not found

buianh0803/YOLOv10_Finetune_Helmet_Safety

buianh0803

2024-06-27T06:05:29Z

0

null

[ "region:us" ]

null

2024-06-27T06:05:29Z

Entry not found

atanu2531/smallpython

atanu2531

2024-06-27T06:07:40Z

0

null

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

null

2024-06-27T06:07:39Z

--- license: gpl-3.0 ---

ridhoo/resyep

ridhoo

2024-06-27T06:15:14Z

0

null

[ "region:us" ]

null

2024-06-27T06:09:02Z

Entry not found

BigHuggyD/alpindale_magnum-72b-v1_exl2_4.0bpw_h8

BigHuggyD

2024-06-27T06:26:31Z

0

transformers

[ "transformers", "safetensors", "qwen2", "text-generation", "chat", "conversational", "en", "zh", "license:other", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "4-bit", "exl2", "region:us" ]

text-generation

2024-06-27T06:09:15Z

--- license: other license_name: tongyi-qianwen license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE language: - en - zh pipeline_tag: text-generation tags: - chat --- ![](https://files.catbox.moe/ngqnb1.png) This is the first in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of [Qwen-2 72B Instruct](https://huggingface.co/Qwen/Qwen2-72B-Instruct). ## Prompting Model has been Instruct tuned with the ChatML formatting. A typical input would look like this: ```py """<|im_start|>user Hi there!<|im_end|> <|im_start|>assistant Nice to meet you!<|im_end|> <|im_start|>user Can I ask a question?<|im_end|> <|im_start|>assistant """ ``` ## Credits This model has been a team effort, credits go to: - [Sao10K](https://huggingface.co/Sao10K) for help with (and cleaning up!) the dataset. - [alpindale](https://huggingface.co/alpindale) for the training. - [kalomaze](https://huggingface.co/kalomaze) for helping with the hyperparameter tuning. - Various other people for their continued help as we tuned the parameters, restarted failed runs. In no particular order: [Doctor Shotgun](https://huggingface.co/Doctor-Shotgun), [Lucy](https://huggingface.co/lucyknada), [Nopm](https://huggingface.co/nopm), [Mango](https://huggingface.co/MangoMango69420), and the rest of the Silly Tilly. And last but not least, we'd like to thank [Kearm](https://twitter.com/Nottlespike) for sponsoring the compute needed to train this model. ## Training The training was done with 55 million tokens of high-quality RP data, over 1.5 epochs. We used 8x [AMD Instinct™ MI300X Accelerators](https://www.amd.com/en/products/accelerators/instinct/mi300/mi300x.html) for the full-parameter fine-tuning of the model. [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) ## Safety ...

gaur3009/Rook-us

gaur3009

2024-06-27T06:20:34Z

0

null

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

null

2024-06-27T06:16:56Z

--- license: unknown ---

starnet/16-star21-06-27

starnet

2024-06-27T06:26:38Z

0

null

[ "any-to-any", "omega", "omegalabs", "bittensor", "agi", "license:mit", "region:us" ]

null

2024-06-27T06:19:36Z

--- license: mit tags: - any-to-any - omega - omegalabs - bittensor - agi --- This is an Any-to-Any model checkpoint for the OMEGA Labs x Bittensor Any-to-Any subnet. Check out the [git repo](https://github.com/omegalabsinc/omegalabs-anytoany-bittensor) and find OMEGA on X: [@omegalabsai](https://x.com/omegalabsai).

akash-43/murad-translator

akash-43

2024-06-27T06:20:31Z

0

null

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

null

2024-06-27T06:20:31Z

--- license: mit ---

37channel/Llama-3-8B-Instruct-LoRA-Full-r8-alpha16-drop0.05-step6-a-loop1

37channel

2024-06-27T06:24:15Z

0

transformers

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

null

2024-06-27T06:22:48Z

--- 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]

rakib72642/PepsodentCore

rakib72642

2024-06-27T06:24:36Z

0

null

[ "region:us" ]

null

2024-06-27T06:22:51Z

Entry not found

twodigit/Mistral-7B-Instruct-v0.3-kowiki_categories-sft-lora-4096-lr1e-5-e1-b4

twodigit

2024-06-27T06:23:31Z

0

transformers

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

null

2024-06-27T06:23:21Z

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

ningxingg/sic

ningxingg

2024-06-27T06:49:41Z

0

null

[ "region:us" ]

null

2024-06-27T06:24:12Z

Entry not found

Gille/BiggerWizardLM-2-7B-Extended-GGUF

Gille

2024-06-27T07:09:53Z

0

null

[ "region:us" ]

null

2024-06-27T06:25:06Z

Entry not found

victimhacker/experiment1

victimhacker

2024-06-27T06:26:48Z

0

null

[ "region:us" ]

null

2024-06-27T06:25:58Z

Entry not found

twodigit/Qwen2-7B-Instruct-kowiki_categories-sft-lora-4096-lr1e-5-e1-b4

twodigit

2024-06-27T06:26:22Z

0

transformers

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

null

2024-06-27T06:26:11Z

--- 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]

Yamadronxzf/Hol

Yamadronxzf

2024-06-27T06:26:25Z

0

null

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

null

2024-06-27T06:26:25Z

--- license: openrail ---

Gatsu0728/G-test

Gatsu0728

2024-06-27T08:07:19Z

0

null

[ "region:us" ]

null

2024-06-27T06:27:30Z

Entry not found

brianfeng/summ

brianfeng

2024-06-27T06:28:24Z

0

null

[ "region:us" ]

null

2024-06-27T06:28:24Z

Entry not found

twodigit/Meta-Llama-3-8B-Instruct-kowiki_categories-sft-lora-4096-lr1e-5-e1-b4

twodigit

2024-06-27T06:28:59Z

0

transformers

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

null

2024-06-27T06:28:48Z

--- 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]

seohyunqkr/MUsE

seohyunqkr

2024-06-27T06:53:43Z

0

null

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

null

2024-06-27T06:30:50Z

--- license: mit ---

Almancy/finetuning-emotion-model-5-v3

Almancy

2024-06-27T08:44:40Z

0

transformers

[ "transformers", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-06-27T06:32:53Z

--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: finetuning-emotion-model-5-v3 results: [] ---  # finetuning-emotion-model-5-v3 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9127 - Accuracy: 0.6077 - F1: 0.6056 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.949 | 1.0 | 2500 | 0.9358 | 0.5976 | 0.5977 | | 0.8216 | 2.0 | 5000 | 0.9127 | 0.6077 | 0.6056 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1

sarpba/llama-3-8b-Instruct-hun

sarpba

2024-07-01T18:11:26Z

0

null

[ "tensorboard", "region:us" ]

null

2024-06-27T06:34:09Z

Entry not found

kaizhu1125/test

kaizhu1125

2024-06-27T06:35:06Z

0

null

[ "region:us" ]

null

2024-06-27T06:35:06Z

Entry not found

KN123/nl2-task-csv.ipynb

KN123

2024-06-27T06:37:02Z

0

transformers

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

null

2024-06-27T06:36:51Z

--- base_model: unsloth/mistral-7b-v0.3-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - **Developed by:** KN123 - **License:** apache-2.0 - **Finetuned from model :** unsloth/mistral-7b-v0.3-bnb-4bit This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)