Instructions to use scales-okn/spacy_judge_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use scales-okn/spacy_judge_model with spaCy:
!pip install https://huggingface.co/scales-okn/spacy_judge_model/resolve/main/spacy_judge_model-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("spacy_judge_model") # Importing as module. import spacy_judge_model nlp = spacy_judge_model.load() - Notebooks
- Google Colab
- Kaggle
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.6,<3.8.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 684830 keys, 684830 unique vectors (300 dimensions) |
| Sources | n/a |
| License | gpl-3.0 |
| Author | n/a |
Label Scheme
View label scheme (2 labels for 1 components)
| Component | Labels |
|---|---|
ner |
HONORARIUM, JUDGE |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
99.20 |
ENTS_P |
98.88 |
ENTS_R |
99.52 |
TOK2VEC_LOSS |
69445.26 |
NER_LOSS |
18046.49 |
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Evaluation results
- NER Precisionself-reported0.989
- NER Recallself-reported0.995
- NER F Scoreself-reported0.992