readme: ---
  language: zh
  ---
  
  # 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
  ```Python
  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
  
  ```bibtex
  @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}
  }
  ```
  