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---
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}
}
```
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