| | --- |
| | 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: |
| |
|
| | ```bibtex |
| | @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}, |
| | } |
| | ``` |
