metadata
language:
- lzh
tags:
- classical chinese
- literary chinese
- ancient chinese
- token-classification
- pos
- dependency-parsing
base_model: KoichiYasuoka/roberta-classical-chinese-large-char
datasets:
- universal_dependencies
license: apache-2.0
pipeline_tag: token-classification
widget:
- text: 子曰學而時習之不亦説乎有朋自遠方來不亦樂乎人不知而不慍不亦君子乎
roberta-classical-chinese-large-upos
Model Description
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.
How to Use
from transformers import AutoTokenizer,AutoModelForTokenClassification
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-classical-chinese-large-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-classical-chinese-large-upos")
or
import esupar
nlp=esupar.load("KoichiYasuoka/roberta-classical-chinese-large-upos")
Reference
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.
See Also
esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models