Question Answering
Transformers
Safetensors
English
pit
SEPIT / README.md
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metadata
license: mit
datasets:
  - U-rara/SEPIT-Data
language:
  - en
base_model:
  - TinyLlama/TinyLlama-1.1B-Chat-v1.0
  - facebook/esm2_t33_650M_UR50D
pipeline_tag: question-answering
library_name: transformers

Model of Paper "SEPIT: Structure-Enhanced Protein Instruction Tuning: Towards General-Purpose Protein Understanding"

Usage

Please refer to https://github.com/U-rara/SEPIT for how to use it.

Citation

If our work is helpful to you, please cite our paper:

@misc{wu2024structureenhancedproteininstructiontuning,
      title={Structure-Enhanced Protein Instruction Tuning: Towards General-Purpose Protein Understanding}, 
      author={Wei Wu and Chao Wang and Liyi Chen and Mingze Yin and Yiheng Zhu and Kun Fu and Jieping Ye and Hui Xiong and Zheng Wang},
      year={2024},
      eprint={2410.03553},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2410.03553}, 
}