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KoichiYasuoka/roberta-large-korean-morph-upos
roberta-large-korean-morph-upos is a token classification model from KoichiYasuoka. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as cc-by-sa-4.0.
This is a RoBERTa model pre-trained on Korean texts for POS-tagging and dependency-parsing, derived from roberta-large-korean-hanja and morphUD-korean. Every morpheme (형태소) is tagged by UPOS(Universal Part-Of-Speech).
Downloads · 30 days
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.model1.4 GB · 51%
From the Hugging Face model README
This is a RoBERTa model pre-trained on Korean texts for POS-tagging and dependency-parsing, derived from roberta-large-korean-hanja and morphUD-korean. Every morpheme (형태소) is tagged by UPOS(Universal Part-Of-Speech).
from transformers import AutoTokenizer,AutoModelForTokenClassification,TokenClassificationPipeline
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-large-korean-morph-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-large-korean-morph-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."))
or
import esupar
nlp=esupar.load("KoichiYasuoka/roberta-large-korean-morph-upos")
print(nlp("홍시 맛이 나서 홍시라 생각한다."))
esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models