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en-ner-en
0xhikae/en-ner-en
en-ner-en 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.
English Named Entity Recognition model built with spaCy.
Access
Public
Updated Apr 3, 2026
Repo size
65 MB
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0
Public
Repo makeup
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Other38.7 MB · 52%
At a glance
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Access
- Public
- Created
- Apr 3, 2026
- Updated
- Apr 3, 2026
- SHA
- ca39ccf9
Try a prompt
Model card
From the Hugging Face model README
en-ner-en
English Named Entity Recognition model built with spaCy.
Labels
| Label | Precision | Recall | F1 |
|---|---|---|---|
| PERSON | 0.955 | 0.978 | 0.966 |
| ORGANIZATION | 0.952 | 0.980 | 0.966 |
| DATE_OF_BIRTH | 0.913 | 0.975 | 0.943 |
| ADDRESS | 0.967 | 0.982 | 0.975 |
| BANK_ACCOUNT | 0.968 | 0.897 | 0.931 |
Architecture
- Pipeline: tok2vec → ner (CNN)
- spaCy version: >=3.8.13,<3.9.0
Install
pip install https://huggingface.co/0xhikae/en-ner-en/resolve/main/en_ner_en-0.1.0.tar.gz
Usage
import spacy
nlp = spacy.load("en_ner_en")
doc = nlp("John Smith lives at 123 Main Street, New York.")
for ent in doc.ents:
print(ent.text, ent.label_)
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Languages
- en
- Created
- Apr 3, 2026
- Updated
- Apr 3, 2026