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Medguanaco Lora 65B GPTQ by nmitchko

 »  All LLMs  »  nmitchko  »  Medguanaco Lora 65B GPTQ   URL Share it on

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  Arxiv:2106.09685   Arxiv:2303.14070   En   Endpoints compatible   Gptq   Lora   Medical   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/nmitchko/medguanaco-lora-65b-GPTQ 

Medguanaco Lora 65B GPTQ Benchmarks

LLME Score: 0.08677
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Medguanaco Lora 65B GPTQ (nmitchko/medguanaco-lora-65b-GPTQ)
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Medguanaco Lora 65B GPTQ Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
medical domain
Primary Use Cases:
question-answering, medical dialogue tasks
Limitations:
May not perform effectively outside the medical domain, Primarily targets the knowledge level of medical students, Not tested in real-world applications, Not a substitute for a doctor's opinion
Considerations:
Must be treated as a research tool only
Additional Notes 
The training data is still under development, with approximately 70% of question-answer pairs believed to be factually correct.
Supported Languages 
en (English)
Training Details 
Data Sources:
Anki flashcards, Wikidoc, StackExchange, ChatDoctor
Data Volume:
Multiple datasets with varying numbers of question-answer pairs
Methodology:
Used LoRA and quantization techniques
Model Architecture:
65B parameters, fine-tuned for medical domain tasks
LLM NameMedguanaco Lora 65B GPTQ
Repository 🤗https://huggingface.co/nmitchko/medguanaco-lora-65b-GPTQ 
Model Size65b
Required VRAM0.3 GB
Updated2025-12-30
Maintainernmitchko
Model Files  0.3 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureAutoModel
Licensecc
Is Biasednone
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesq_proj|v_proj
LoRA Alpha64
LoRA Dropout0.05
R Param32

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Note: green Score (e.g. "73.2") means that the model is better than nmitchko/medguanaco-lora-65b-GPTQ.

Rank the Medguanaco Lora 65B GPTQ 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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