metadata
language:
- zh
pipeline_tag: fill-mask
widget:
- text: ba黎系[MASK]国的首都
example_title: Adversarial Attack Test
RoCBert
Introduction
RoCBert is a pretrained Chinese language model that is robust under various forms of adversarial attacks proposed by WeChatAI in 2022,
More detail: https://aclanthology.org/2022.acl-long.65.pdf
Pretrained code: https://github.com/sww9370/RoCBert
How to use
# pip install transformers>=4.25.1
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("weiweishi/roc-bert-base-zh")
model = AutoModel.from_pretrained("weiweishi/roc-bert-base-zh")
Citation
@inproceedings{su2022rocbert,
title={RoCBert: Robust Chinese Bert with Multimodal Contrastive Pretraining},
author={Su, Hui and Shi, Weiwei and Shen, Xiaoyu and Xiao, Zhou and Ji, Tuo and Fang, Jiarui and Zhou, Jie},
booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
pages={921--931},
year={2022}
}