| language: | |
| - "ja" | |
| tags: | |
| - "japanese" | |
| - "masked-lm" | |
| license: "cc-by-sa-4.0" | |
| pipeline_tag: "fill-mask" | |
| mask_token: "[MASK]" | |
| widget: | |
| - text: "日本に着いたら[MASK]を訪ねなさい。" | |
| # 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. | |