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en_pipeline
Vishveshwara/en_pipeline
en_pipeline is a token classification model from Vishveshwara. Use it when you need labels on individual words, such as names. It is set up for spacy.
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1.3 GB
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Other659 MB · 52%
At a glance
- Task
- Token Classification
- Library
- spacy
- Access
- Public
- Created
- Jun 11, 2024
- Updated
- Jun 11, 2024
- SHA
- 925a9d1b
Try a prompt
Model card
From the Hugging Face model README
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.4,<3.8.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 514157 keys, 514157 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
<details> <summary>View label scheme (19 labels for 1 components)</summary>| Component | Labels |
|---|---|
ner | Act, Address, Court, EffectiveDate, PII_Ref, Parties, Percentage, Price, Principal, Ratio, Regulation, RenewalTerm, Rent, RevolvingCredit, Role, Salary, Shares, TerminationDate, Title |
Accuracy
| Type | Score |
|---|---|
ENTS_F | 88.57 |
ENTS_P | 87.19 |
ENTS_R | 89.99 |
TOK2VEC_LOSS | 77252.72 |
NER_LOSS | 131420.51 |
- Task
- Token Classification
- Library
- spacy
- Languages
- en
- Created
- Jun 11, 2024
- Updated
- Jun 11, 2024