bert-large-japanese-upos
Model Description
This is a BERT model pre-trained on Japanese Wikipedia texts for POS-tagging and dependency-parsing, derived from bert-large-japanese-char-extended. Every short-unit-word is tagged by UPOS (Universal Part-Of-Speech).
How to Use
import torch
from transformers import AutoTokenizer,AutoModelForTokenClassification
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/bert-large-japanese-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-large-japanese-upos")
s="国境の長いトンネルを抜けると雪国であった。"
p=[model.config.id2label[q] for q in torch.argmax(model(tokenizer.encode(s,return_tensors="pt"))["logits"],dim=2)[0].tolist()[1:-1]]
print(list(zip(s,p)))
or
import esupar
nlp=esupar.load("KoichiYasuoka/bert-large-japanese-upos")
print(nlp("国境の長いトンネルを抜けると雪国であった。"))
See Also
esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
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Base model
tohoku-nlp/bert-large-japanese-char