readme: ---
  language: 
  - "zh"
  thumbnail: "https://raw.githubusercontent.com/SIKU-BERT/SikuBERT/main/appendix/sikubert.png"
  tags:
  - "chinese"
  - "classical chinese"
  - "literary chinese"
  - "ancient chinese"
  - "bert"
  - "roberta"
  - "pytorch"
  inference: false 
  license: "apache-2.0"
  ---
  # SikuBERT
  ## Model description
  ![SikuBERT](https://raw.githubusercontent.com/SIKU-BERT/SikuBERT-for-digital-humanities-and-classical-Chinese-information-processing/main/appendix/sikubert.png)
  Digital humanities research needs the support of large-scale corpus and high-performance ancient Chinese natural language processing tools. The pre-training language model has greatly improved the accuracy of text mining in English and modern Chinese texts. At present, there is an urgent need for a pre-training model specifically for the automatic processing of ancient texts. We used the verified high-quality “Siku Quanshu” full-text corpus as the training set, based on the BERT deep language model architecture, we constructed the SikuBERT and SikuRoBERTa pre-training language models for intelligent processing tasks of ancient Chinese. 
  ## How to use
  ```python
  from transformers import AutoTokenizer, AutoModel
  tokenizer = AutoTokenizer.from_pretrained("SIKU-BERT/sikubert")
  model = AutoModel.from_pretrained("SIKU-BERT/sikubert")
  ```
  ## About Us
  We are from Nanjing Agricultural University.
  > Created with by SIKU-BERT [![Github icon](https://cdn0.iconfinder.com/data/icons/octicons/1024/mark-github-32.png)](https://github.com/SIKU-BERT/SikuBERT-for-digital-humanities-and-classical-Chinese-information-processing) 