README.md

metadata

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。

deberta-base-japanese-aozora

Model Description

This is a DeBERTa(V2) model pre-trained on 青空文庫 texts. NVIDIA A100-SXM4-40GB took 36 hours 44 minutes for training. You can fine-tune deberta-base-japanese-aozora for downstream tasks, such as POS-tagging, dependency-parsing, and so on.

How to Use

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

Reference

安岡孝一: 青空文庫DeBERTaモデルによる国語研長単位係り受け解析, 東洋学へのコンピュータ利用, 第35回研究セミナー (2022年7月), pp.29-43.