Edit model card

deberta-base-korean-upos

Model Description

This is a DeBERTa(V3) model pre-trained on Korean texts for POS-tagging and dependency-parsing, derived from deberta-v3-base-korean. 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/deberta-base-korean-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/deberta-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."))

or

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

See Also

esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models

Downloads last month
2
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for KoichiYasuoka/deberta-base-korean-upos

Finetuned
(3)
this model

Dataset used to train KoichiYasuoka/deberta-base-korean-upos