README.md

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}
}