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| title: README |
| emoji: 🏆 |
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| colorTo: pink |
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| We are dedicated to LLMs that serve the agricultural sector. Specifically, due to the current lack of fine-tuning datasets for LLMs in crop science, |
| we have released our CROP dataset, which is a large open-source dataset with over 210K Q&A pairs. Furthermore, to provide a high-quality evaluation standard for this vertical domain, |
| we have introduced the CROP benchmark, which is a large open-source dataset with 5045 multiple-choice questions. |
| We hope our work will advance the field of LLMs in agricultural production and contribute to solving hunger issues. |
|
|
| ## Note |
| **Our work is accepted by NeurIPS2024 Dataset & Benchmark Track.** |
| All datasets and benchmarks are open-sourced. You can see our project website at **https://github.com/RenqiChen/The_Crop** for more details about our work. |
| |
| ## BibTeX & Citation |
| |
| If you find our codes and datasets useful, please consider citing our work: |
| |
| ```bibtex |
| @inproceedings{zhangempowering, |
| title={Empowering and Assessing the Utility of Large Language Models in Crop Science}, |
| author={Zhang, Hang and Sun, Jiawei and Chen, Renqi and Liu, Wei and Yuan, Zhonghang and Zheng, Xinzhe and Wang, Zhefan and Yang, Zhiyuan and Yan, Hang and Zhong, Han-Sen and others}, |
| booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track} |
| } |
| ``` |
