|
--- |
|
language: |
|
- "ja" |
|
tags: |
|
- "japanese" |
|
- "token-classification" |
|
- "pos" |
|
- "dependency-parsing" |
|
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。" |
|
--- |
|
|
|
# deberta-base-japanese-upos |
|
|
|
## Model Description |
|
|
|
This is a DeBERTa(V2) model pre-trained on 青空文庫 texts for POS-tagging and dependency-parsing, derived from [deberta-base-japanese-aozora](https://huggingface.co/KoichiYasuoka/deberta-base-japanese-aozora). Every short-unit-word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech). |
|
|
|
## How to Use |
|
|
|
```py |
|
import torch |
|
from transformers import AutoTokenizer,AutoModelForTokenClassification |
|
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/deberta-base-japanese-upos") |
|
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/deberta-base-japanese-upos") |
|
s="国境の長いトンネルを抜けると雪国であった。" |
|
t=tokenizer.tokenize(s) |
|
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(t,p))) |
|
``` |
|
|
|
or |
|
|
|
```py |
|
import esupar |
|
nlp=esupar.load("KoichiYasuoka/deberta-base-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](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models |
|
|
|
|
