metadata
language:
- ja
tags:
- japanese
- token-classification
- pos
- wikipedia
datasets:
- universal_dependencies
license: cc-by-sa-4.0
pipeline_tag: token-classification
widget:
- text: 国境の長いトンネルを抜けると雪国であった。
bert-base-japanese-luw-upos
Model Description
This is a BERT model pre-trained on Japanese Wikipedia texts for POS-tagging, derived from bert-base-japanese-char-extended. Every long-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-base-japanese-luw-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-base-japanese-luw-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)))
See Also
esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models