This is a RoBERTa model pre-trained on Classical Chinese texts for POS-tagging and dependency-parsing, derived from
roberta-classical-chinese-large-char. Every word is tagged by
UPOS (Universal Part-Of-Speech) and
FEATS.
1from transformers import AutoTokenizer,AutoModelForTokenClassification
2tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-classical-chinese-large-upos")
3model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-classical-chinese-large-upos")
1import esupar
2nlp=esupar.load("KoichiYasuoka/roberta-classical-chinese-large-upos")
Koichi Yasuoka:
Universal Dependencies Treebank of the Four Books in Classical Chinese, DADH2019: 10th International Conference of Digital Archives and Digital Humanities (December 2019), pp.20-28.
esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
