SFT Datasets of ChemVLM

MMChem Series

Each sub-directory is a subset in arrow format of our training dataset, including both image bytes and conversations, you can download them all and load with datasets.load_from_disk.

Citation

@inproceedings{li2025chemvlm,
  title={Chemvlm: Exploring the power of multimodal large language models in chemistry area},
  author={Li, Junxian and Zhang, Di and Wang, Xunzhi and Hao, Zeying and Lei, Jingdi and Tan, Qian and Zhou, Cai and Liu, Wei and Yang, Yaotian and Xiong, Xinrui and others},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={39},
  number={1},
  pages={415--423},
  year={2025}
}