This is a BERT model pre-trained on Vietnamese texts for POS-tagging and dependency-parsing, derived from vibert-base-cased. Every word is tagged by UPOS(Universal Part-Of-Speech).

How to Use

from transformers import AutoTokenizer,AutoModelForTokenClassification,TokenClassificationPipeline
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/bert-base-vietnamese-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-base-vietnamese-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("Hai cái đầu thì tốt hơn một."))

import esupar
nlp=esupar.load("KoichiYasuoka/bert-base-vietnamese-upos")
print(nlp("Hai cái đầu thì tốt hơn một."))

KoichiYasuoka/bert-base-vietnamese-upos

bert-base-vietnamese-upos

Model Description

How to Use

See Also

KoichiYasuoka/
bert-base-vietnamese-upos