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}
}