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en_pipeline
FarhanQ101/en_pipeline
en_pipeline is a token classification model from FarhanQ101. Use it when you need labels on individual words, such as names. It is set up for spacy.
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11.7 MB
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At a glance
- Task
- Token Classification
- Library
- spacy
- Access
- Public
- Created
- Nov 7, 2023
- Updated
- Nov 7, 2023
- SHA
- 84a76ade
Try a prompt
Model card
From the Hugging Face model README
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.1,<3.8.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
<details> <summary>View label scheme (8 labels for 1 components)</summary>| Component | Labels |
|---|---|
ner | AMOUNT, AVAILABLE_BAL, DATE, OTHER_ACC_ADD, RECEPIENT_NAME, TIME, UPI_REF_ID, USER_ACC_ADD |
Accuracy
| Type | Score |
|---|---|
ENTS_F | 99.70 |
ENTS_P | 99.70 |
ENTS_R | 99.70 |
TOK2VEC_LOSS | 8615.31 |
NER_LOSS | 9620.54 |
- Task
- Token Classification
- Library
- spacy
- Languages
- en
- Created
- Nov 7, 2023
- Updated
- Nov 7, 2023