Token Classification
Transformers
PyTorch
Japanese
deberta-v2
japanese
wikipedia
pos
dependency-parsing
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/deberta-large-japanese-wikipedia-ud-goeswith")
model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/deberta-large-japanese-wikipedia-ud-goeswith")Quick Links
deberta-large-japanese-wikipedia-ud-goeswith
Model Description
This is a DeBERTa(V2) model pretrained on Japanese Wikipedia and 青空文庫 texts for POS-tagging and dependency-parsing (using goeswith for subwords), derived from deberta-large-japanese-wikipedia-luw-upos and UD_Japanese-GSDLUW.
How to Use
from transformers import pipeline
nlp=pipeline("universal-dependencies","KoichiYasuoka/deberta-large-japanese-wikipedia-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple")
print(nlp("全学年にわたって小学校の国語の教科書に挿し絵が用いられている"))
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KoichiYasuoka/deberta-large-japanese-wikipedia-ud-goeswith")