This is a RoBERTa model pre-trained on Korean texts for POS-tagging and dependency-parsing, derived from roberta-base-korean-hanja. Every word (어절) is tagged by UPOS(Universal Part-Of-Speech).

How to Use

from transformers import AutoTokenizer,AutoModelForTokenClassification,TokenClassificationPipeline
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-korean-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-base-korean-upos")
pipeline=TokenClassificationPipeline(tokenizer=tokenizer,model=model,aggregation_strategy="simple")
nlp=lambda x:[(x[t["start"]:t["end"]],t["entity_group"]) for t in pipeline(x)]
print(nlp("홍시 맛이 나서 홍시라 생각한다."))

import esupar
nlp=esupar.load("KoichiYasuoka/roberta-base-korean-upos")
print(nlp("홍시 맛이 나서 홍시라 생각한다."))

KoichiYasuoka/roberta-base-korean-upos

roberta-base-korean-upos

Model Description

How to Use

See Also

KoichiYasuoka/
roberta-base-korean-upos