Medalpaca Lora 30B 8bit by medalpaca

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  Arxiv:2106.09685   Arxiv:2303.14070   8bit   En   Endpoints compatible   Lora   Medical   Quantized   Region:us

Medalpaca Lora 30B 8bit Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Medalpaca Lora 30B 8bit (medalpaca/medalpaca-lora-30b-8bit)
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Medalpaca Lora 30B 8bit Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
medical domain tasks
Primary Use Cases:
question-answering, medical dialogue tasks
Limitations:
May not perform effectively outside medical domain, Primarily targets medical students' knowledge level, Not tested in real-world applications
Considerations:
It should not substitute a doctor's opinion.
Supported Languages 
en (English)
Training Details 
Data Sources:
Anki flashcards, Wikidoc, StackExchange, ChatDoctor dataset
Methodology:
LoRA fine-tuning and quantization
Model Architecture:
Based on LLaMA
LLM NameMedalpaca Lora 30B 8bit
Repository ๐Ÿค—https://huggingface.co/medalpaca/medalpaca-lora-30b-8bit 
Model Size30b
Required VRAM0.2 GB
Updated2025-08-18
Maintainermedalpaca
Model Files  0.2 GB
Supported Languagesen
Quantization Type8bit
Model ArchitectureAutoModel
Licensecc
Is Biasednone
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesq_proj|k_proj|v_proj|o_proj
LoRA Alpha16
LoRA Dropout0.1
R Param16

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Note: green Score (e.g. "73.2") means that the model is better than medalpaca/medalpaca-lora-30b-8bit.

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