
# roberta-base-japanese-aozora-char

## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts with character tokenizer. You can fine-tune `roberta-base-japanese-aozora-char` for downstream tasks, such as [POS-tagging](https://huggingface.co/KoichiYasuoka/roberta-base-japanese-char-luw-upos), [dependency-parsing](https://huggingface.co/KoichiYasuoka/roberta-base-japanese-aozora-ud-head), and so on.

## How to Use

```py
from transformers import AutoTokenizer,AutoModelForMaskedLM
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-japanese-aozora-char")
model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-base-japanese-aozora-char")
```

## 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.


{"language": ["ja"], "license": "cc-by-sa-4.0", "tags": ["japanese", "masked-lm"], "pipeline_tag": "fill-mask", "mask_token": "[MASK]", "widget": [{"text": "\u65e5\u672c\u306b\u7740\u3044\u305f\u3089[MASK]\u3092\u8a2a\u306d\u306a\u3055\u3044\u3002"}]}
transformers pytorch roberta fill-mask japanese masked-lm ja license:cc-by-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #fill-mask #japanese #masked-lm #ja #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 


# roberta-base-japanese-aozora-char

## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts with character tokenizer. You can fine-tune 'roberta-base-japanese-aozora-char' for downstream tasks, such as POS-tagging, dependency-parsing, and so on.

## How to Use



## 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.


# roberta-base-japanese-aozora-char ## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts with character tokenizer. You can fine-tune 'roberta-base-japanese-aozora-char' for downstream tasks, such as POS-tagging, dependency-parsing, and so on. ## How to Use ## 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.
TAGS
#transformers #pytorch #roberta #fill-mask #japanese #masked-lm #ja #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 # roberta-base-japanese-aozora-char ## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts with character tokenizer. You can fine-tune 'roberta-base-japanese-aozora-char' for downstream tasks, such as POS-tagging, dependency-parsing, and so on. ## How to Use ## 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.
passage: TAGS
#transformers #pytorch #roberta #fill-mask #japanese #masked-lm #ja #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
# roberta-base-japanese-aozora-char## Model Description

This is a RoBERTa model pre-trained on 青空文庫 texts with character tokenizer. You can fine-tune 'roberta-base-japanese-aozora-char' for downstream tasks, such as POS-tagging, dependency-parsing, and so on.## How to Use## 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.