HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale
✨ Updates
🩻 PubMedVision
- PubMedVision is a large-scale, high-quality medical VQA dataset, constructed from the image-text pairs from PubMed and reformatted using GPT-4V.
|
# Data |
Download |
| PubMedVision Dataset |
1,294,062 |
HF Link |
- PubMedVision could significantly improve the medical multimodal capabilities of MLLMs such as LLaVA-v1.5.
|
VQA-RAD |
SLAKE |
PathVQA |
PMC-VQA |
| LLaVA-v1.6-34B |
58.6 |
67.3 |
59.1 |
44.4 |
| LLaVA-v1.5-LLaMA3-8B |
54.2 |
59.4 |
54.1 |
36.4 |
| LLaVA-v1.5-LLaMA3-8B + PubMedVision |
63.8 |
74.5 |
59.9 |
52.7 |
|
OmniMedVQA |
MMMU Health & Medicine (Test Set) |
| LLaVA-v1.6-34B |
61.4 |
48.8 |
| LLaVA-v1.5-LLaMA3-8B |
48.8 |
38.2 |
| LLaVA-v1.5-LLaMA3-8B + PubMedVision |
75.1 |
49.1 |
👨⚕️ HuatuoGPT-Vision
HuatuoGPT-Vision is our medical multimodal LLMs, built on PubMedVision.
Model Access
| Our model is available on Huggingface in two versions: |
|
Backbone |
Checkpoint |
| HuatuoGPT-Vision-7B |
Qwen2-7B |
HF Link |
| HuatuoGPT-Vision-34B |
Yi-1.5-34B |
HF Link |
Model Usage
Chat via the command line:
python cli.py --model_dir path-to-huatuogpt-vision-model
Inference using our ChatBot:
query = 'What does the picture show?'
image_paths = ['image_path1']
from cli import HuatuoChatbot
bot = HuatuoChatbot(path-to-huatuogpt-vision-model)
output = bot.inference(query, image_paths)
print(output) # Prints the output of the model
Performance of Medical Multimodal
|
VQA-RAD |
SLAKE |
PathVQA |
PMC-VQA |
| LLaVA-Med-7B |
51.4 |
48.6 |
56.8 |
24.7 |
| LLaVA-v1.6-34B |
58.6 |
67.3 |
59.1 |
44.4 |
| HuatuoGPT-Vision-7B |
63.7 |
76.2 |
57.9 |
54.3 |
| HuatuoGPT-Vision-34B |
68.1 |
76.9 |
63.5 |
58.2 |
|
OmniMedVQA |
MMMU Health & Medicine (Test Set) |
| LLaVA-Med-7B |
44.5 |
36.9 |
| LLaVA-v1.6-34B |
61.4 |
48.8 |
| HuatuoGPT-Vision-7B |
74.0 |
50.6 |
| HuatuoGPT-Vision-34B |
76.9 |
54.4 |
🩺 HuatuoGPT Series
Explore our HuatuoGPT series:
- HuatuoGPT: Taming Language Models to Be a Doctor
- HuatuoGPT-II: One-stage Training for Medical Adaptation of LLMs
- HuatuoGPT-Vision: Injecting Medical Visual Knowledge into Multimodal LLMs at Scale
Citation
@misc{chen2024huatuogptvisioninjectingmedicalvisual,
title={HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale},
author={Junying Chen and Ruyi Ouyang and Anningzhe Gao and Shunian Chen and Guiming Hardy Chen and Xidong Wang and Ruifei Zhang and Zhenyang Cai and Ke Ji and Guangjun Yu and Xiang Wan and Benyou Wang},
year={2024},
eprint={2406.19280},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2406.19280},
}