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DISC MedLLM by Flmc

 »  All LLMs  »  Flmc  »  DISC MedLLM   URL Share it on

  905   
  Arxiv:2308.14346   Autotrain compatible   Baichuan   Custom code   Dataset:flmc/disc-med-sft   Endpoints compatible   Medical   Pytorch   Region:us   Sharded   Zh
Model Card on HF 🤗: https://huggingface.co/Flmc/DISC-MedLLM 

DISC MedLLM Benchmarks

LLME Score: 0.12133
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
DISC MedLLM (Flmc/DISC-MedLLM)
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DISC MedLLM Parameters and Internals

Model Type 
conversational
Use Cases 
Areas:
conversational healthcare, medical consultations
Primary Use Cases:
medical consultations, treatment inquiries
Limitations:
The model may not produce accurate or reliable information.
Considerations:
Designed exclusively for research and testing.
Additional Notes 
Model weights may differ from demo. Quantization may degrade performance.
Supported Languages 
zh (high)
Training Details 
Data Sources:
MedDialog, cMedQA2, CMeKG, MedMCQA, MOSS-SFT, Alpaca-GPT4-zh
Data Volume:
470k examples
Methodology:
Goal-oriented strategy and human-in-the-loop
Safety Evaluation 
Ethical Considerations:
Users should critically assess generated information; no warranty on accuracy or reliability.
Input Output 
Accepted Modalities:
text
LLM NameDISC MedLLM
Repository 🤗https://huggingface.co/Flmc/DISC-MedLLM 
Required VRAM26.5 GB
Updated2025-08-18
MaintainerFlmc
Model Typebaichuan
Model Files  10.0 GB: 1-of-3   9.9 GB: 2-of-3   6.6 GB: 3-of-3
Supported Languageszh
Model ArchitectureBaichuanForCausalLM
Licenseapache-2.0
Model Max Length4096
Transformers Version4.31.0
Tokenizer ClassBaichuanTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size64000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Flmc/DISC-MedLLM.

Rank the DISC MedLLM 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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