metadata
language:
- zh
tags:
- chinese
- token-classification
- pos
- dependency-parsing
base_model: IDEA-CCNL/Erlangshen-DeBERTa-v2-710M-Chinese
datasets:
- universal_dependencies
license: apache-2.0
pipeline_tag: token-classification
deberta-xlarge-chinese-erlangshen-upos
Model Description
This is a DeBERTa(V2) model pre-trained on Chinese texts (both simplified and traditional) for POS-tagging and dependency-parsing, derived from Erlangshen-DeBERTa-v2-710M-Chinese. Every word is tagged by UPOS (Universal Part-Of-Speech).
How to Use
from transformers import AutoTokenizer,AutoModelForTokenClassification
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/deberta-xlarge-chinese-erlangshen-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/deberta-xlarge-chinese-erlangshen-upos")
or
import esupar
nlp=esupar.load("KoichiYasuoka/deberta-xlarge-chinese-erlangshen-upos")
See Also
esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models