Update README.md

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+---
+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"
+license: "apache-2.0"
+---
+# SikuBERT
+## Model description
+![SikuBERT](https://raw.githubusercontent.com/SIKU-BERT/SikuBERT/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)