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en_nerry_rel_tok2vec
hjianganthony/en_nerry_rel_tok2vec
en_nerry_rel_tok2vec is a token classification model from hjianganthony. Use it when you need labels on individual words, such as names. It is set up for spacy.
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14.1 MB
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.json10.4 MB · 42%
At a glance
- Task
- Token Classification
- Library
- spacy
- Access
- Public
- Created
- Nov 12, 2023
- Updated
- Nov 12, 2023
- SHA
- 4739cf01
Try a prompt
Model card
From the Hugging Face model README
RE with tok2vec
| Feature | Description |
|---|---|
| Name | en_nerry_rel_tok2vec |
| Version | 2.0.0 |
| spaCy | >=3.6.1,<3.7.0 |
| Default Pipeline | tok2vec, ner, relation_extractor |
| Components | tok2vec, ner, relation_extractor |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | HjAnthony |
Label Scheme
<details> <summary>View label scheme (4 labels for 2 components)</summary>| Component | Labels |
|---|---|
ner | CRIME, PERSON, PROCECUTION |
relation_extractor | INVOVLED_IN |
Accuracy
| Type | Score |
|---|---|
ENTS_F | 70.42 |
ENTS_P | 54.35 |
ENTS_R | 100.00 |
REL_MICRO_P | 55.56 |
REL_MICRO_R | 100.00 |
REL_MICRO_F | 71.43 |
TOK2VEC_LOSS | 0.00 |
RELATION_EXTRACTOR_LOSS | 105.57 |
- Task
- Token Classification
- Library
- spacy
- Languages
- en
- Created
- Nov 12, 2023
- Updated
- Nov 12, 2023