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cling1024/google-gemma-2b-1728004459	cling1024	"2024-10-04T01:14:28Z"	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "region:us" ]	null	"2024-10-04T01:14:19Z"	--- base_model: google/gemma-2b library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.13.0
RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf	RichardErkhov	"2024-10-04T01:32:57Z"	null	[ "gguf", "region:us" ]	null	"2024-10-04T01:15:21Z"	Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) Qwen2.5-0.5B-Instruct-ymg-finetuned-0925 - GGUF - Model creator: https://huggingface.co/GOODYEONSU/ - Original model: https://huggingface.co/GOODYEONSU/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925/ \| Name \| Quant method \| Size \| \| ---- \| ---- \| ---- \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q2_K.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q2_K.gguf) \| Q2_K \| 0.39GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ3_XS.gguf) \| IQ3_XS \| 0.39GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ3_S.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ3_S.gguf) \| IQ3_S \| 0.39GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q3_K_S.gguf) \| Q3_K_S \| 0.39GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ3_M.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ3_M.gguf) \| IQ3_M \| 0.39GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q3_K.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q3_K.gguf) \| Q3_K \| 0.4GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q3_K_M.gguf) \| Q3_K_M \| 0.4GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q3_K_L.gguf) \| Q3_K_L \| 0.42GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ4_XS.gguf) \| IQ4_XS \| 0.4GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_0.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_0.gguf) \| Q4_0 \| 0.4GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.IQ4_NL.gguf) \| IQ4_NL \| 0.4GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_K_S.gguf) \| Q4_K_S \| 0.45GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_K.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_K.gguf) \| Q4_K \| 0.46GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_K_M.gguf) \| Q4_K_M \| 0.46GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_1.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q4_1.gguf) \| Q4_1 \| 0.43GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_0.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_0.gguf) \| Q5_0 \| 0.46GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_K_S.gguf) \| Q5_K_S \| 0.48GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_K.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_K.gguf) \| Q5_K \| 0.49GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_K_M.gguf) \| Q5_K_M \| 0.49GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_1.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q5_1.gguf) \| Q5_1 \| 0.49GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q6_K.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q6_K.gguf) \| Q6_K \| 0.61GB \| \| [Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q8_0.gguf](https://huggingface.co/RichardErkhov/GOODYEONSU_-_Qwen2.5-0.5B-Instruct-ymg-finetuned-0925-gguf/blob/main/Qwen2.5-0.5B-Instruct-ymg-finetuned-0925.Q8_0.gguf) \| Q8_0 \| 0.63GB \| Original model description: --- library_name: transformers license: apache-2.0 base_model: Qwen/Qwen2.5-0.5B-Instruct tags: - trl - sft - generated_from_trainer model-index: - name: Qwen2.5-0.5B-Instruct-ymg-finetuned-0925 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. --> # Qwen2.5-0.5B-Instruct-ymg-finetuned-0925 This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 3 - gradient_accumulation_steps: 8 - total_train_batch_size: 384 - total_eval_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 3 ### Training results ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1
Xu-Ouyang/Meta-Llama-3-8B-int2-GPTQ-wikitext2	Xu-Ouyang	"2024-10-04T01:32:15Z"	transformers	[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "2-bit", "gptq", "region:us" ]	text-generation	"2024-10-04T01:15:58Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
cling1024/Qwen-Qwen1.5-0.5B-1728004568	cling1024	"2024-10-04T01:16:13Z"	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:Qwen/Qwen1.5-0.5B", "base_model:adapter:Qwen/Qwen1.5-0.5B", "region:us" ]	null	"2024-10-04T01:16:08Z"	--- base_model: Qwen/Qwen1.5-0.5B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.13.0
dearyoungjo/whisperkit_coreml_mdcnb1	dearyoungjo	"2024-10-04T01:19:01Z"	null	[ "license:mit", "region:us" ]	null	"2024-10-04T01:16:13Z"	--- license: mit ---
llavallava/llava15_7b_DPO_h0.0_h0.1-llava15_7b_h0.0_h0.1_caption_1step-20241003_181656	llavallava	"2024-10-04T01:16:57Z"	null	[ "region:us" ]	null	"2024-10-04T01:16:56Z"	Entry not found
samuellau0802/MEMIT-786-gemma	samuellau0802	"2024-10-04T01:17:04Z"	null	[ "region:us" ]	null	"2024-10-04T01:17:04Z"	Entry not found
llavallava/llava15_7b_DPO_h0.0_h0.1-llava15_7b_h0.0_h0.1_caption_1step-20241003_181731	llavallava	"2024-10-04T01:24:39Z"	null	[ "safetensors", "llava_llama", "region:us" ]	null	"2024-10-04T01:17:31Z"	Entry not found
shaeysamuel/sos-lora	shaeysamuel	"2024-10-04T01:17:38Z"	null	[ "region:us" ]	null	"2024-10-04T01:17:38Z"	--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md ---
SMTruong/results	SMTruong	"2024-10-04T01:21:25Z"	transformers	[ "transformers", "safetensors", "t5", "text2text-generation", "generated_from_trainer", "base_model:google/flan-t5-small", "base_model:finetune:google/flan-t5-small", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text2text-generation	"2024-10-04T01:18:16Z"	--- library_name: transformers license: apache-2.0 base_model: google/flan-t5-small tags: - generated_from_trainer model-index: - name: results 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. --> # results This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1664 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:---------------:\| \| 0.1994 \| 1.0 \| 4091 \| 0.1716 \| \| 0.1917 \| 2.0 \| 8182 \| 0.1664 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.19.1
cling1024/Qwen-Qwen1.5-1.8B-1728004711	cling1024	"2024-10-04T01:18:35Z"	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:Qwen/Qwen1.5-1.8B", "base_model:adapter:Qwen/Qwen1.5-1.8B", "region:us" ]	null	"2024-10-04T01:18:31Z"	--- base_model: Qwen/Qwen1.5-1.8B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.13.0
forcemultiplier/gpqa-syngen-gemma2-2b	forcemultiplier	"2024-10-04T01:28:29Z"	null	[ "safetensors", "region:us" ]	null	"2024-10-04T01:19:30Z"	# GPQA Generator: Fine-tuned Gemma 2B for Google GPQA (Graduate-Level Google-Proof Q&A Benchmark) dataset ## Model Details - Model Type: Language Model - Base Model: unsloth/gemma-2-2b-bnb-4bit - Fine-tuned by: [Your Organization/Name] - License: [Specify the license] This model is a fine-tuned version of the Gemma 2B base model, specifically tailored to Google GPQA (Graduate-Level Google-Proof Q&A Benchmark) dataset. It produces graduate-level, context-rich multiple-choice questions along with one correct answer, three incorrect answers, and an explanation. ## Intended Use This model is designed for educational content creators, assessment developers, and researchers who need to generate complex, Google-proof multiple-choice questions across various academic disciplines. ### Primary Use Cases: - Generating challenging assessment questions for advanced students - Creating content for educational platforms and applications - Assisting in the development of standardized tests - Supporting research in question generation and educational assessment ## How to Use ### Setting Up 1. Clone the repository containing the model and scripts. 2. Ensure you have the required dependencies installed (httpx, transformers, etc.). ### Running the Model 1. Start the vLLM server: ``` ./run_vllm_2b.sh ``` 2. Generate questions using the `generate.py` script: For a single category: ``` python generate.py --category "Your Category" --depth 4 ``` To use predefined categories: ``` python generate.py --use-array --depth 4 ``` ### Configuration - Modify the `CATEGORIES_TO_PROCESS` list in the script to add or change predefined categories. - Adjust the `max_depth` parameter to control the depth of subcategory exploration. - The script uses multi-threading for efficient processing. Adjust `num_threads` in `process_categories()` if needed. ## Sample Output Here's an example of the generated output: ```json { "question": "A developer is working on a large project that uses Mercurial version control. They need to merge a branch containing bug fixes from another team. What is the recommended approach to avoid merging conflicts?", "answer": "The developer should: \n1. Create a new branch from the source directory. \n2. Compare the history of the branches. \n3. Resolve conflicts manually. \n4. Commit the changes. ", "incorrect_answer_1": "Merge the branches directly.", "incorrect_answer_2": "Skip the merge process altogether.", "incorrect_answer_3": "Use a third-party tool like Git.", "explanation": "Merging branches in Mercurial requires careful consideration to avoid conflicts. Here's a breakdown of the reasoning: \n1. Branch Creation: Creating a new branch allows the developer to isolate the changes from the other team without affecting the base branch.\n2. Conflict Detection: Comparing the histories of the branches helps identify potential conflicts that may arise during the merge.\n3. Conflict Resolution: Manual conflict resolution is essential to ensure the merge is successful. Mercurial provides tools like \"diff\" and \"merge\" commands for this purpose.\n4. Committing Changes: Once the merge is complete, the developer should commit the changes to their new branch.", "subcategories": ["Version Control", "Mercurial", "Merge Conflicts"], "category": "Mercurial", "depth": 0 } ``` ## Limitations - The model generates questions based on its training data, which may not always reflect the most current information in rapidly evolving fields. - While designed to be "Google-proof," the effectiveness may vary depending on the specific topic and how information is presented online. - The quality and accuracy of generated questions should be reviewed by subject matter experts before use in formal assessments. ## Ethical Considerations - Users should be aware of potential biases in the generated content and review questions for fairness and inclusivity. - The model should not be used to generate misleading or factually incorrect information. - Respect copyright and intellectual property rights when using generated content. ## Citation If you use this model in your research or applications, please cite it as follows: ``` [Citation information to be added] ``` ## Contact For questions, feedback, or support, please contact [Your Contact Information].
flavioferlin/vit-base-oxford-iiit-pets	flavioferlin	"2024-10-04T01:19:31Z"	null	[ "region:us" ]	null	"2024-10-04T01:19:31Z"	Entry not found
RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf	RichardErkhov	"2024-10-04T01:20:27Z"	null	[ "region:us" ]	null	"2024-10-04T01:20:27Z"	Entry not found
paulmaksimovich/Mistral-Small-Instruct-2409-Q4_K_M-GGUF	paulmaksimovich	"2024-10-04T01:31:46Z"	transformers	[ "transformers", "gguf", "llama-cpp", "gguf-my-repo", "en", "fr", "de", "es", "it", "pt", "zh", "ja", "ru", "ko", "base_model:mistralai/Mistral-Small-Instruct-2409", "base_model:quantized:mistralai/Mistral-Small-Instruct-2409", "license:other", "endpoints_compatible", "region:us" ]	null	"2024-10-04T01:21:25Z"	Invalid username or password.
Xu-Ouyang/Qwen2.5-1.5B-int4-GPTQ-wikitext2	Xu-Ouyang	"2024-10-04T01:22:31Z"	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "gptq", "region:us" ]	text-generation	"2024-10-04T01:21:31Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
cling1024/google-gemma-2b-1728004895	cling1024	"2024-10-04T01:21:43Z"	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "region:us" ]	null	"2024-10-04T01:21:35Z"	--- base_model: google/gemma-2b library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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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] ### Framework versions - PEFT 0.13.0
samuellau0802/MEMIT-787-gemma	samuellau0802	"2024-10-04T01:22:16Z"	null	[ "region:us" ]	null	"2024-10-04T01:22:16Z"	Entry not found
cling1024/Qwen-Qwen1.5-0.5B-1728005002	cling1024	"2024-10-04T01:23:26Z"	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:Qwen/Qwen1.5-0.5B", "base_model:adapter:Qwen/Qwen1.5-0.5B", "region:us" ]	null	"2024-10-04T01:23:22Z"	--- base_model: Qwen/Qwen1.5-0.5B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.13.0
ajinkgupta/Apti-llama-1B	ajinkgupta	"2024-10-04T01:34:21Z"	null	[ "safetensors", "llama", "region:us" ]	null	"2024-10-04T01:23:42Z"	Temporary Redirect. Redirecting to /ketuai/Apti-llama-1B/resolve/main/README.md
Agement/guhhoodie	Agement	"2024-10-04T01:23:45Z"	null	[ "region:us" ]	null	"2024-10-04T01:23:44Z"	--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md language: - en tags: - flux - diffusers - lora - replicate base_model: "black-forest-labs/FLUX.1-dev" pipeline_tag: text-to-image # widget: # - text: >- # prompt # output: # url: https://... instance_prompt: GUH --- # Guhhoodie <!-- <Gallery /> --> Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train ## Trigger words You should use `GUH` to trigger the image generation. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('Agement/guhhoodie', weight_name='lora.safetensors') image = pipeline('your prompt').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
mylesgoose/Llama-3.2-90B-Vision-Instruct-abliterated	mylesgoose	"2024-10-04T01:23:47Z"	null	[ "license:other", "region:us" ]	null	"2024-10-04T01:23:47Z"	--- license: other license_name: meta license_link: LICENSE ---
evgmaslov/Qwen2.5-Coder-7B-Instruct-cars	evgmaslov	"2024-10-04T01:24:20Z"	null	[ "region:us" ]	null	"2024-10-04T01:24:20Z"	Entry not found
cling1024/Qwen-Qwen1.5-1.8B-1728005144	cling1024	"2024-10-04T01:25:48Z"	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:Qwen/Qwen1.5-1.8B", "base_model:adapter:Qwen/Qwen1.5-1.8B", "region:us" ]	null	"2024-10-04T01:25:45Z"	--- base_model: Qwen/Qwen1.5-1.8B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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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. 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spacepxl/ml-depth-pro	spacepxl	"2024-10-04T01:28:57Z"	null	[ "region:us" ]	null	"2024-10-04T01:26:04Z"	https://github.com/apple/ml-depth-pro Converted to .safetensors
pixxiesang/1	pixxiesang	"2024-10-04T01:26:36Z"	null	[ "license:mit", "region:us" ]	null	"2024-10-04T01:26:36Z"	--- license: mit ---
samuellau0802/MEMIT-788-gemma	samuellau0802	"2024-10-04T01:27:29Z"	null	[ "region:us" ]	null	"2024-10-04T01:27:29Z"	Entry not found
pouya12/pouyak12	pouya12	"2024-10-04T01:30:42Z"	null	[ "license:openrail", "region:us" ]	null	"2024-10-04T01:27:38Z"	--- license: openrail ---
kairovann/kairo	kairovann	"2024-10-04T01:28:18Z"	null	[ "region:us" ]	null	"2024-10-04T01:28:18Z"	Entry not found
lonen78u/painttoon	lonen78u	"2024-10-04T01:28:28Z"	diffusers	[ "diffusers", "text-to-image", "flux", "lora", "template:sd-lora", "fluxgym", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]	text-to-image	"2024-10-04T01:28:28Z"	Invalid username or password.
pranay27sy/maritime-tag-prediction-Llama-3.2-3B-Instruct-v3	pranay27sy	"2024-10-04T01:31:46Z"	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	"2024-10-04T01:28:40Z"	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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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. 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cling1024/google-gemma-2b-1728005329	cling1024	"2024-10-04T01:28:54Z"	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "region:us" ]	null	"2024-10-04T01:28:49Z"	--- base_model: google/gemma-2b library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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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] ### Framework versions - PEFT 0.13.0
davidkim205/hades-9b-keyword	davidkim205	"2024-10-04T01:29:45Z"	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	"2024-10-04T01:29:26Z"	--- library_name: transformers tags: [] --- # hades-9b-keyword ## License Use of this model requires company approval. Please contact AI@2digit.io. For more details, please refer to the website below: https://2digit.io/#contactus ## Evaluation \| \| task \| file \| recall \| precision \| f1 \| top1_score \| (0, 5](20) \| (15, 20](2) \| (20, 25](5) \| (25, 30](5) \| (30, 35](4) \| (35, 40](2) \| (40, 45](1) \| (45, 50](1) \| \|---:\|:--------\|:--------------------------------------------------------------------\|---------:\|------------:\|-----:\|-------------:\|-------------:\|--------------:\|--------------:\|--------------:\|--------------:\|--------------:\|--------------:\|--------------:\| \| 0 \| keyword \| hades-9b-keyword-keyword_testset.jsonl \| 0.61 \| 0.44 \| 0.47 \| 0.55 \| 0.69 \| 0.25 \| 0.62 \| 0.54 \| 0.6 \| 0.76 \| 0.33 \| 0.35 \| \| 1 \| keyword \| hades-7b-keyword_testset.jsonl \| 0.39 \| 0.43 \| 0.35 \| 0.49 \| 0.48 \| 0.1 \| 0.42 \| 0.35 \| 0.24 \| 0.35 \| 0.33 \| 0 \| \| 2 \| keyword \| Meta-Llama-3-8B-Instruct-keyword_23k-sft-lora-keyword_testset.jsonl \| 0.24 \| 0.28 \| 0.21 \| 0.39 \| 0.32 \| 0.18 \| 0.27 \| 0.11 \| 0.1 \| 0.16 \| 0.14 \| 0 \|
elpahan/model	elpahan	"2024-10-04T01:34:39Z"	transformers	[ "transformers", "gguf", "text-generation-inference", "unsloth", "llama", "en", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	"2024-10-04T01:30:34Z"	--- base_model: unsloth/meta-llama-3.1-8b-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - gguf --- # Uploaded model - Developed by: elpahan - License: apache-2.0 - Finetuned from model : unsloth/meta-llama-3.1-8b-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
latiao1999/google-gemma-2b-1728005446	latiao1999	"2024-10-04T01:30:53Z"	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "region:us" ]	null	"2024-10-04T01:30:46Z"	--- base_model: google/gemma-2b library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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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] ### Framework versions - PEFT 0.12.0
RichardErkhov/DavidAU_-_L3-Lumimaid-12.2B-v0.1-OAS-Instruct-gguf	RichardErkhov	"2024-10-04T01:31:12Z"	null	[ "region:us" ]	null	"2024-10-04T01:31:12Z"	Entry not found
solmetria/Nila	solmetria	"2024-10-04T01:31:22Z"	null	[ "region:us" ]	null	"2024-10-04T01:31:19Z"	Entry not found
dawon62/hkcode-mb-en-ko	dawon62	"2024-10-04T01:31:44Z"	null	[ "region:us" ]	null	"2024-10-04T01:31:44Z"	--- library_name: transformers tags: - trl - sft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
samuellau0802/MEMIT-789-gemma	samuellau0802	"2024-10-04T01:32:37Z"	null	[ "region:us" ]	null	"2024-10-04T01:32:37Z"	Entry not found
yjmsvma/nl_dc_mod_v2	yjmsvma	"2024-10-04T01:34:41Z"	transformers	[ "transformers", "safetensors", "distilbert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	"2024-10-04T01:33:58Z"	--- 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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