
# roberta-base-japanese-char-luw-upos

## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts for POS-tagging and dependency-parsing, derived from [roberta-base-japanese-aozora-char](https://huggingface.co/KoichiYasuoka/roberta-base-japanese-aozora-char). Every long-unit-word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech) and [FEATS](https://universaldependencies.org/u/feat/).

## How to Use

```py
from transformers import AutoTokenizer,AutoModelForTokenClassification,TokenClassificationPipeline
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-japanese-char-luw-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-base-japanese-char-luw-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("国境の長いトンネルを抜けると雪国であった。"))
```

or

```py
import esupar
nlp=esupar.load("KoichiYasuoka/roberta-base-japanese-char-luw-upos")
print(nlp("国境の長いトンネルを抜けると雪国であった。"))
```

## Reference

安岡孝一: [Transformersと国語研長単位による日本語係り受け解析モデルの製作](http://id.nii.ac.jp/1001/00216223/), 情報処理学会研究報告, Vol.2022-CH-128, No.7 (2022年2月), pp.1-8.

## See Also

[esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models


{"language": ["ja"], "license": "cc-by-sa-4.0", "tags": ["japanese", "token-classification", "pos", "dependency-parsing"], "datasets": ["universal_dependencies"], "pipeline_tag": "token-classification", "widget": [{"text": "\u56fd\u5883\u306e\u9577\u3044\u30c8\u30f3\u30cd\u30eb\u3092\u629c\u3051\u308b\u3068\u96ea\u56fd\u3067\u3042\u3063\u305f\u3002"}]}
transformers pytorch roberta token-classification japanese pos dependency-parsing ja dataset:universal_dependencies license:cc-by-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #token-classification #japanese #pos #dependency-parsing #ja #dataset-universal_dependencies #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 


# roberta-base-japanese-char-luw-upos

## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts for POS-tagging and dependency-parsing, derived from roberta-base-japanese-aozora-char. Every long-unit-word is tagged by UPOS (Universal Part-Of-Speech) and FEATS.

## How to Use



or



## Reference

安岡孝一: Transformersと国語研長単位による日本語係り受け解析モデルの製作, 情報処理学会研究報告, Vol.2022-CH-128, No.7 (2022年2月), pp.1-8.

## See Also

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


# roberta-base-japanese-char-luw-upos ## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts for POS-tagging and dependency-parsing, derived from roberta-base-japanese-aozora-char. Every long-unit-word is tagged by UPOS (Universal Part-Of-Speech) and FEATS. ## How to Use



or ## Reference

安岡孝一: Transformersと国語研長単位による日本語係り受け解析モデルの製作, 情報処理学会研究報告, Vol.2022-CH-128, No.7 (2022年2月), pp.1-8. ## See Also

esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
TAGS
#transformers #pytorch #roberta #token-classification #japanese #pos #dependency-parsing #ja #dataset-universal_dependencies #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 # roberta-base-japanese-char-luw-upos ## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts for POS-tagging and dependency-parsing, derived from roberta-base-japanese-aozora-char. Every long-unit-word is tagged by UPOS (Universal Part-Of-Speech) and FEATS. ## How to Use



or ## Reference

安岡孝一: Transformersと国語研長単位による日本語係り受け解析モデルの製作, 情報処理学会研究報告, Vol.2022-CH-128, No.7 (2022年2月), pp.1-8. ## See Also

esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
passage: TAGS
#transformers #pytorch #roberta #token-classification #japanese #pos #dependency-parsing #ja #dataset-universal_dependencies #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
# roberta-base-japanese-char-luw-upos## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts for POS-tagging and dependency-parsing, derived from roberta-base-japanese-aozora-char. Every long-unit-word is tagged by UPOS (Universal Part-Of-Speech) and FEATS.## How to Use



or## Reference

安岡孝一: Transformersと国語研長単位による日本語係り受け解析モデルの製作, 情報処理学会研究報告, Vol.2022-CH-128, No.7 (2022年2月), pp.1-8.## See Also

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