metadata
language:
- zh
tags:
- chinese
- token-classification
- pos
- wikipedia
- dependency-parsing
datasets:
- universal_dependencies
license: apache-2.0
pipeline_tag: token-classification
chinese-roberta-base-upos
Model Description
This is a BERT model pre-trained on Chinese Wikipedia texts (both simplified and traditional) for POS-tagging and dependency-parsing, derived from chinese-roberta-wwm-ext. Every word is tagged by UPOS (Universal Part-Of-Speech).
How to Use
from transformers import AutoTokenizer,AutoModelForTokenClassification
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/chinese-roberta-base-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/chinese-roberta-base-upos")
or
import esupar
nlp=esupar.load("KoichiYasuoka/chinese-roberta-base-upos")
See Also
esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models