Manhph2211/Q-HEART
<div align="center" style="font-size: 1.5em;"> <strong>Q-HEART: ECG Question Answering via Knowledge-Informed Multimodal LLMs (ECAI 2025)</strong> </div>
<div align="center"> <a href="https://github.com/manhph2211/Q-HEART/"><img src="https://img.shields.io/badge/Website-QHEART WebPage-blue?style=for-the-badge"></a> <a href="https://arxiv.org/pdf/2505.06296"><img src="https://img.shields.io/badge/arxiv-Paper-red?style=for-the-badge"></a> <a href="https://huggingface.co/Manhph2211/Q-HEART"><img src="https://img.shields.io/badge/Checkpoint-%F0%9F%A4%97%20Hugging%20Face-White?style=for-the-badge"></a> </div>
<div align="center"> <a href="https://github.com/manhph2211/" target="blank">Hung Manh Pham</a>   <a href="" target="blank">Jialu Tang</a>   <a href="https://aqibsaeed.github.io/" target="blank">Aaqib Saeed</a>   <a href="https://www.dongma.info/" target="blank">Dong Ma</a>   </div> <br>
Usage
After we have access to meta-llama/Llama-3.2-1B-Instruct model and install suitable transformers package version, we can run:
# transformers==4.43.3 accelerate==1.0.1 peft==0.13.2
from transformers import AutoModel
model = AutoModel.from_pretrained("Manhph2211/Q-HEART", trust_remote_code=True, dtype="auto")Or
git clone https://github.com/manhph2211/Q-HEART.git && cd Q-HEART
conda create -n qheart python=3.9
conda activate qheart
pip install torch --index-url https://download.pytorch.org/whl/cu118
pip install -r requirements.txtDownload the checkpoint from here and place it at ckpts/pytorch_model.bin, then run evaluation:
python main.py --model_type meta-llama/Llama-3.2-1B-Instruct --mapping_type TransformerCitation
@article{pham2025q,
title={Q-Heart: ECG Question Answering via Knowledge-Informed Multimodal LLMs},
author={Pham, Hung Manh and Tang, Jialu and Saeed, Aaqib and Ma, Dong},
journal={arXiv preprint arXiv:2505.06296},
year={2025}
}
@inproceedings{pham2025qheart,
title = {Q-HEART: ECG Question Answering via Knowledge-Informed Multimodal LLMs},
author = {Pham, Hung Manh and Tang, Jialu and Saeed, Aaqib and Ma, Dong},
booktitle = {Proceedings of the European Conference on Artificial Intelligence (ECAI)},
series = {Frontiers in Artificial Intelligence and Applications},
volume = {413},
pages = {4545--4552},
year = {2025},
publisher = {IOS Press},
doi = {10.3233/FAIA251356}
}<div align="center"> Please refer to our <a href="https://github.com/manhph2211/Q-HEART">GitHub repo</a> for more details! </div>
