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.
from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SIKU-BERT/sikubert") model = AutoModel.from_pretrained("SIKU-BERT/sikubert")
We are from Nanjing Agricultural University.
Select AutoNLP in the “Train” menu to fine-tune this model automatically.
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