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  ---
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- base_model:
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- - BioMistral/BioMistral-7B
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- - mistralai/Mistral-7B-Instruct-v0.1
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- library_name: transformers
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- tags:
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- - mergekit
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- - merge
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- - dare
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- - medical
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- - biology
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- license: apache-2.0
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- datasets:
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- - pubmed
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  language:
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  - en
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  - fr
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  - pl
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  - ro
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  - de
 
 
 
 
 
 
 
 
 
 
 
 
 
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  pipeline_tag: text-generation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # BioMistral-7B-mistral7instruct-dare
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@@ -147,3 +250,17 @@ Arxiv : [https://arxiv.org/abs/2402.10373](https://arxiv.org/abs/2402.10373)
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  **CAUTION!** Both direct and downstream users need to be informed about the risks, biases, and constraints inherent in the model. While the model can produce natural language text, our exploration of its capabilities and limitations is just beginning. In fields such as medicine, comprehending these limitations is crucial. Hence, we strongly advise against deploying this model for natural language generation in production or for professional tasks in the realm of health and medicine.
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
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  language:
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  - en
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  - fr
 
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  - pl
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  - ro
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  - de
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+ license: apache-2.0
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+ library_name: transformers
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+ tags:
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+ - mergekit
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+ - merge
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+ - dare
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+ - medical
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+ - biology
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+ datasets:
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+ - pubmed
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+ base_model:
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+ - BioMistral/BioMistral-7B
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+ - mistralai/Mistral-7B-Instruct-v0.1
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  pipeline_tag: text-generation
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+ model-index:
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+ - name: BioMistral-7B-DARE
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+ results:
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: AI2 Reasoning Challenge (25-Shot)
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+ type: ai2_arc
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+ config: ARC-Challenge
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+ split: test
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+ args:
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+ num_few_shot: 25
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+ metrics:
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+ - type: acc_norm
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+ value: 58.28
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BioMistral/BioMistral-7B-DARE
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: HellaSwag (10-Shot)
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+ type: hellaswag
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+ split: validation
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+ args:
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+ num_few_shot: 10
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+ metrics:
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+ - type: acc_norm
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+ value: 79.87
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BioMistral/BioMistral-7B-DARE
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MMLU (5-Shot)
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+ type: cais/mmlu
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+ config: all
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 57.34
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BioMistral/BioMistral-7B-DARE
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: TruthfulQA (0-shot)
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+ type: truthful_qa
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+ config: multiple_choice
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+ split: validation
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: mc2
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+ value: 55.61
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BioMistral/BioMistral-7B-DARE
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: Winogrande (5-shot)
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+ type: winogrande
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+ config: winogrande_xl
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+ split: validation
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 76.09
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BioMistral/BioMistral-7B-DARE
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: GSM8k (5-shot)
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+ type: gsm8k
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+ config: main
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 15.01
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BioMistral/BioMistral-7B-DARE
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+ name: Open LLM Leaderboard
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  ---
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  # BioMistral-7B-mistral7instruct-dare
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  **CAUTION!** Both direct and downstream users need to be informed about the risks, biases, and constraints inherent in the model. While the model can produce natural language text, our exploration of its capabilities and limitations is just beginning. In fields such as medicine, comprehending these limitations is crucial. Hence, we strongly advise against deploying this model for natural language generation in production or for professional tasks in the realm of health and medicine.
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+
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+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_BioMistral__BioMistral-7B-DARE)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |57.03|
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+ |AI2 Reasoning Challenge (25-Shot)|58.28|
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+ |HellaSwag (10-Shot) |79.87|
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+ |MMLU (5-Shot) |57.34|
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+ |TruthfulQA (0-shot) |55.61|
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+ |Winogrande (5-shot) |76.09|
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+ |GSM8k (5-shot) |15.01|
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+