# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/deberta-base-ainu-ud-goeswith")
model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/deberta-base-ainu-ud-goeswith", device_map="auto")Quick Links
deberta-base-ainu-ud-goeswith
Model Description
This is a DeBERTa(V2) model pre-trained on Ainu texts (in カタカナ, Roman, and Кириллица) for POS-tagging and dependency-parsing (using goeswith for subwords), derived from deberta-base-ainu-upos.
How to Use
from transformers import pipeline
nlp=pipeline("universal-dependencies","KoichiYasuoka/deberta-base-ainu-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple")
print(nlp("itak=as awa pon rupne aynu ene itaki"))
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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Model tree for KoichiYasuoka/deberta-base-ainu-ud-goeswith
Base model
KoichiYasuoka/deberta-base-ainu Finetuned
KoichiYasuoka/deberta-base-ainu-upos
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KoichiYasuoka/deberta-base-ainu-ud-goeswith")