# 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) 
{"language": ["zh"], "license": "apache-2.0", "tags": ["chinese", "classical chinese", "literary chinese", "ancient chinese", "bert", "roberta", "pytorch"], "thumbnail": "https://raw.githubusercontent.com/SIKU-BERT/SikuBERT/main/appendix/sikubert.png", "inference": false}
transformers pytorch bert fill-mask chinese classical chinese literary chinese ancient chinese roberta zh license:apache-2.0 autotrain_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #chinese #classical chinese #literary chinese #ancient chinese #roberta #zh #license-apache-2.0 #autotrain_compatible #region-us 

# SikuBERT
## Model description
!SikuBERT
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

## About Us
We are from Nanjing Agricultural University.
> Created with by SIKU-BERT ![Github icon](URL 
# SikuBERT ## Model description
!SikuBERT
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 ## About Us
We are from Nanjing Agricultural University.
> Created with by SIKU-BERT ![Github icon](URL
TAGS
#transformers #pytorch #bert #fill-mask #chinese #classical chinese #literary chinese #ancient chinese #roberta #zh #license-apache-2.0 #autotrain_compatible #region-us 
 # SikuBERT ## Model description
!SikuBERT
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 ## About Us
We are from Nanjing Agricultural University.
> Created with by SIKU-BERT ![Github icon](URL
passage: TAGS
#transformers #pytorch #bert #fill-mask #chinese #classical chinese #literary chinese #ancient chinese #roberta #zh #license-apache-2.0 #autotrain_compatible #region-us 
# SikuBERT## Model description
!SikuBERT
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## About Us
We are from Nanjing Agricultural University.
> Created with by SIKU-BERT ![Github icon](URL