readme: ---
  language: 
    - zh
  license: apache-2.0
  ---
  # Mengzi-BERT base fin model (Chinese)
  Continue trained mengzi-bert-base with 20G financial news and research reports. Masked language modeling(MLM), part-of-speech(POS) tagging and sentence order prediction(SOP) are used as training task.
  
  [Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese](https://arxiv.org/abs/2110.06696)
  
  ## Usage
  ```python
  from transformers import BertTokenizer, BertModel
  tokenizer = BertTokenizer.from_pretrained("Langboat/mengzi-bert-base-fin")
  model = BertModel.from_pretrained("Langboat/mengzi-bert-base-fin")
  ```
  
  ## Citation
  If you find the technical report or resource is useful, please cite the following technical report in your paper.
  ```
  @misc{zhang2021mengzi,
        title={Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese}, 
        author={Zhuosheng Zhang and Hanqing Zhang and Keming Chen and Yuhang Guo and Jingyun Hua and Yulong Wang and Ming Zhou},
        year={2021},
        eprint={2110.06696},
        archivePrefix={arXiv},
        primaryClass={cs.CL}
  }
  
  ```