Instructions to use KoichiYasuoka/deberta-base-ainu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/deberta-base-ainu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KoichiYasuoka/deberta-base-ainu")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/deberta-base-ainu") model = AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/deberta-base-ainu") - Notebooks
- Google Colab
- Kaggle
deberta-base-ainu
Model Description
This is a DeBERTa(V2) model pre-trained on Ainu texts written in カタカナ, Roman, and Кириллица. You can fine-tune deberta-base-ainu 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-ainu")
model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/deberta-base-ainu")
Reference
安岡孝一: ローマ字・カタカナ・キリル文字併用アイヌ語RoBERTa・DeBERTaモデルの開発, 情報処理学会研究報告, Vol.2023-CH-131『人文科学とコンピュータ』, No.7 (2023年2月18日), pp.1-7.
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