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BioMistral 7B AWQ QGS128 W4 GEMV by BioMistral

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  Arxiv:2402.10373   4-bit   Autotrain compatible   Awq   Biology   Conversational Dataset:mit-han-lab/pile-val-b...   Dataset:pubmed   De   En   Endpoints compatible   Es   Fr   Gemv   It   Medical   Mistral   Pl   Pt   Quantization   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/BioMistral/BioMistral-7B-AWQ-QGS128-W4-GEMV 

BioMistral 7B AWQ QGS128 W4 GEMV Benchmarks

LLME Score: 0.1388
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
BioMistral 7B AWQ QGS128 W4 GEMV (BioMistral/BioMistral-7B-AWQ-QGS128-W4-GEMV)
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BioMistral 7B AWQ QGS128 W4 GEMV Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
research, biomedical domain
Applications:
medical question-answering, multilingual evaluation
Primary Use Cases:
research tool for medical LLM efficacy testing
Limitations:
Not suitable for production use in health or medical professional settings
Considerations:
Use with caution, especially outside English contexts.
Additional Notes 
Not recommended for medical decision making without extensive further validation.
Supported Languages 
fr (C1), en (C2), pt (B2), pl (B2), it (B1), es (A2), de (A2)
Training Details 
Data Sources:
PubMed Central Open Access
Methodology:
Further pre-trained on PubMed Central data
Context Length:
2048
Hardware Used:
CNRS Jean Zay French HPC
Model Architecture:
Mistral-based
Responsible Ai Considerations 
Fairness:
Multilingual evaluation to assess model biases and generalization across languages.
Input Output 
Input Format:
Text prompts
Accepted Modalities:
text
Output Format:
Text
Performance Tips:
Ensure comprehensive model evaluation before deployment.
LLM NameBioMistral 7B AWQ QGS128 W4 GEMV
Repository 🤗https://huggingface.co/BioMistral/BioMistral-7B-AWQ-QGS128-W4-GEMV 
Model Size7b
Required VRAM4.2 GB
Updated2025-08-19
MaintainerBioMistral
Model Typemistral
Model Files  4.2 GB
Supported Languagesfr en pt pl it es de
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than BioMistral/BioMistral-7B-AWQ-QGS128-W4-GEMV.

Rank the BioMistral 7B AWQ QGS128 W4 GEMV Capabilities

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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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