ERNIE-1.0

Introduction

ERNIE (Enhanced Representation through kNowledge IntEgration) is proposed by Baidu in 2019, which is designed to learn language representation enhanced by knowledge masking strategies i.e. entity-level masking and phrase-level masking. Experimental results show that ERNIE achieve state-of-the-art results on five Chinese natural language processing tasks including natural language inference, semantic similarity, named entity recognition, sentiment analysis and question answering.

More detail: https://arxiv.org/abs/1904.09223

Released Model Info

This released pytorch model is converted from the officially released PaddlePaddle ERNIE model and a series of experiments have been conducted to check the accuracy of the conversion.

• Official PaddlePaddle ERNIE repo: https://github.com/PaddlePaddle/ERNIE
• Pytorch Conversion repo: https://github.com/nghuyong/ERNIE-Pytorch

How to use

from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("nghuyong/ernie-1.0-base-zh")
model = AutoModel.from_pretrained("nghuyong/ernie-1.0-base-zh")

Citation

@article{sun2019ernie,
  title={Ernie: Enhanced representation through knowledge integration},
  author={Sun, Yu and Wang, Shuohuan and Li, Yukun and Feng, Shikun and Chen, Xuyi and Zhang, Han and Tian, Xin and Zhu, Danxiang and Tian, Hao and Wu, Hua},
  journal={arXiv preprint arXiv:1904.09223},
  year={2019}
}