Skip to content

Latest commit

 

History

History
117 lines (73 loc) · 4.22 KB

README.md

File metadata and controls

117 lines (73 loc) · 4.22 KB
Raw

Pre-trained Multimodal Large Language Model Enhances Dermatological Diagnosis using SkinGPT-4

Juexiao Zhou, Xiaonan He, Liyuan Sun, Jiannan Xu, Xiuying Chen, Yuetan Chu, Longxi Zhou, Xingyu Liao, Bin Zhang, Shawn Afvari, Xin Gao

King Abdullah University of Science and Technology, KAUST

Installation

conda env create -f environment.yml
conda activate skingpt4_llama2
conda install -c conda-forge mamba=1.4.7
conda install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.8 -c pytorch -c nvidia

Download our trained weights

Our previous trained weights for skin disease diagnosis with only base dataset and Llama2 could be downloaded at skingpt4_llama2_13bchat_base_pretrain_stage2.pth. Then modify line 10 at SkinGPT-4-llama2/eval_configs/skingpt4_eval_llama2_13bchat.yaml to be the path of SkinGPT-4 weight.

Our previous trained weights for skin disease diagnosis with only step-1 dataset and Vicuna could be downloaded at skingpt4_vicuna_v1.pth. Then modify line 11 at SkinGPT-4-llama2/eval_configs/skingpt4_eval_vicuna.yaml to be the path of SkinGPT-4 weight.

Please note:

  • The released trained model above cannot be used for skin disease diagnosis, they can only be used for testing code.

  • The latest model trained with both public skin disease datasets and the proprietary skin disease dataset based on falcon-40b-instruct (deprecated) and llama-2-13b-chat-hf (code published only) are not publicly available currently due to privacy issues.

  • Please feel free to keep in touch with [email protected] and [email protected] for potential collaboration.

Prepare weight for LLMs

Llama2 Version

git clone https://huggingface.co/meta-llama/Llama-2-13b-chat-hf

Then modify line 16 at SkinGPT-4-llama2/skingpt4/configs/models/skingpt4_llama2_13bchat.yaml to be the path of Llama-2-13b-chat-hf.

Vicuna Version

# download Vicuna’s **delta** weight
git lfs install
git clone https://huggingface.co/lmsys/vicuna-13b-delta-v0

# get llama-13b model
git clone https://huggingface.co/huggyllama/llama-13b

pip install git+https://github.com/lm-sys/[email protected]
pip install transformers==4.28.0

python -m fastchat.model.apply_delta --base ./llama-13b --target ./vicuna --delta ./vicuna-13b-delta-v0

Then modify line 16 at SkinGPT-4-llama2/skingpt4/configs/models/skingpt4_vicuna.yaml to be the path of vicuna.

Launching Demo Locally

Llama2 Version

python demo.py --cfg-path eval_configs/skingpt4_eval_llama2_13bchat.yaml  --gpu-id 0

Vicuna Version

python demo.py --cfg-path eval_configs/skingpt4_eval_vicuna.yaml  --gpu-id 0

Illustraion of SkinGPT-4

Figure_1

Examples of Skin disease diagnosis

Figure_3

Clinical Evaluation

Figure_4

Acknowledgement

  • MiniGPT-4 This repo is developped on MiniGPT-4, an awesome repo for vision-language chatbot!
  • Lavis
  • Vicuna
  • Falcon
  • Llama 2

Citation

Our paper has been accepted by Nature Communications.

image-20240708131953458

If you find SkinGPT-4 to be helpful in your research or applications, please cite SkinGPT-4 using this BibTeX:

@article{zhou2024pre,
  title={Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4},
  author={Zhou, Juexiao and He, Xiaonan and Sun, Liyuan and Xu, Jiannan and Chen, Xiuying and Chu, Yuetan and Zhou, Longxi and Liao, Xingyu and Zhang, Bin and Afvari, Shawn and others},
  journal={Nature Communications},
  volume={15},
  number={1},
  pages={5649},
  year={2024},
  publisher={Nature Publishing Group UK London}
}