Phi Med V1 by justinj92

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  Autotrain compatible   Custom code   Dataset:bi55/medtext   En   Endpoints compatible   Lora   Medical   Phi-msft   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF ๐Ÿค—: https://huggingface.co/justinj92/phi-med-v1 

Phi Med V1 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Phi Med V1 (justinj92/phi-med-v1)

Phi Med V1 Parameters and Internals

Model Type 
SLM
Use Cases 
Areas:
Testing the effectiveness of Finetuning SLMs
Supported Languages 
en (English)
Training Details 
Data Sources:
MedText Dataset from HuggingFace
Methodology:
SFT using HF Transformers
Hardware Used:
A10 GPU VMs [2x24GB A10]
Responsible Ai Considerations 
Mitigation Strategies:
Model can still hallucinate.
LLM NamePhi Med V1
Repository ๐Ÿค—https://huggingface.co/justinj92/phi-med-v1 
Model Size2.8b
Required VRAM11.1 GB
Updated2024-12-22
Maintainerjustinj92
Model Files  0.0 GB   4.9 GB: 1-of-3   4.9 GB: 2-of-3   1.3 GB: 3-of-3   0.0 GB
Supported Languagesen
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Is Biasednone
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesf1|f2|Wqkv
LoRA Alpha16
LoRA Dropout0.05
R Param16

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Note: green Score (e.g. "73.2") means that the model is better than justinj92/phi-med-v1.

Rank the Phi Med V1 Capabilities

๐Ÿ†˜ 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! ๐ŸŒŸ

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 v20241217