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ja-ner-ja
0xhikae/ja-ner-ja
ja-ner-ja is a token classification model from 0xhikae. Use it when you need labels on individual words, such as names. It is set up for spacy. The card lists the license as mit.
Japanese Named Entity Recognition model built with spaCy.
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Access
- Public
- Created
- Apr 3, 2026
- Updated
- Apr 3, 2026
- SHA
- fe0a3afd
Model card
From the Hugging Face model README
ja-ner-ja
Japanese Named Entity Recognition model built with spaCy.
Labels
| Label | Precision | Recall | F1 |
|---|---|---|---|
| PERSON | 0.950 | 0.949 | 0.949 |
| DATE_OF_BIRTH | 0.872 | 0.872 | 0.872 |
| ADDRESS | 0.904 | 0.967 | 0.934 |
| ORGANIZATION | 0.929 | 0.828 | 0.876 |
| BANK_ACCOUNT | 0.947 | 0.857 | 0.900 |
Architecture
- Pipeline: tok2vec → ner
- spaCy version: >=3.8.13,<3.9.0
Install
pip install https://huggingface.co/0xhikae/ja-ner-ja/resolve/main/ja_ner_ja-0.2.0-py3-none-any.whl
Usage
import spacy
nlp = spacy.load("ja_ner_ja")
doc = nlp("田中太郎は東京都渋谷区に住んでいます。")
for ent in doc.ents:
print(ent.text, ent.label_)
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Languages
- ja
- Created
- Apr 3, 2026
- Updated
- Apr 3, 2026