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A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

License: MIT License

Python 98.25% Shell 1.75%

p-tuning's Introduction

P-tuning

โ— News

๐ŸŒŸ [2021-10-15] P-tuning v2 is out! Check our Github repo.

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

Xiao Liu*, Yanan Zheng*, Zhengxiao Du, Ming Ding, Yujie Qian, Zhilin Yang, Jie Tang

You may be also interested in our another work GLM: All NLP Tasks Are Generation Tasks: A General Pretraining Framework

How to use our code

We have released the code and datasets for LAMA and few-shot SuperGLUE (32-dev) experiments. Please check README.md and requirement.txt in the corresponding subdirectories for details.

The LAMA and FewGLUE_32dev datasets are available. The LAMA dataset should be placed in ./data directory, and the SuperGLUE dataset should be placed in the ./ (project root) directory.

Citation

If you find our work useful, please cite the following paper:

    @article{liu2021gpt,
    title={GPT Understands, Too},
    author={Liu, Xiao and Zheng, Yanan and Du, Zhengxiao and Ding, Ming and Qian, Yujie and Yang, Zhilin and Tang, Jie},
    journal={arXiv:2103.10385},
    year={2021}
    }

p-tuning's People

Contributors

xiao9905 avatar zheng-yanan avatar

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