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BioMistral 7B GGUF by BioMistral

 »  All LLMs  »  BioMistral  »  BioMistral 7B GGUF   URL Share it on

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  Arxiv:2402.10373   Autotrain compatible   Biology   Conversational   Dataset:pubmed   De   En   Endpoints compatible   Es   Fr   Ggml   Gguf   It   Medical   Mistral   Nl   Pl   Pt   Q2   Quantized   Region:us   Ro
Model Card on HF 🤗: https://huggingface.co/BioMistral/BioMistral-7B-GGUF 

BioMistral 7B GGUF Benchmarks

LLME Score: 0.14997
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
BioMistral 7B GGUF (BioMistral/BioMistral-7B-GGUF)
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BioMistral 7B GGUF Parameters and Internals

Model Type 
text-generation
Use Cases 
Limitations:
Model is not suited for professional health and medical tasks without further testing.
Considerations:
Thorough alignment with specific use cases and further testing recommended.
Additional Notes 
Automatically translated and evaluated benchmarks in 7 other languages; First large-scale multilingual evaluation for medical LLMs.
Supported Languages 
languages_offered (:[)
Training Details 
Data Sources:
PubMed Central Open Access (CC0, CC BY, CC BY-SA, and CC BY-ND)
Context Length:
2048
Hardware Used:
CNRS Jean Zay French HPC
LLM NameBioMistral 7B GGUF
Repository 🤗https://huggingface.co/BioMistral/BioMistral-7B-GGUF 
Model Size7b
Required VRAM1 GB
Updated2025-09-23
MaintainerBioMistral
Model Typemistral
Model Files  2.7 GB   1.0 GB   3.5 GB   3.2 GB   2.8 GB   4.4 GB   4.1 GB   5.1 GB   5.0 GB   5.9 GB   7.7 GB
Supported Languagesfr en de nl es pt pl ro it
GGML QuantizationYes
GGUF QuantizationYes
Quantization Typegguf|ggml|q2|q4_k|q5_k
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.0
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than BioMistral/BioMistral-7B-GGUF.

Rank the BioMistral 7B GGUF Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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