Instructions to use jcorrie/en_extract_definitions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use jcorrie/en_extract_definitions with spaCy:
!pip install https://huggingface.co/jcorrie/en_extract_definitions/resolve/main/en_extract_definitions-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_extract_definitions") # Importing as module. import en_extract_definitions nlp = en_extract_definitions.load() - Notebooks
- Google Colab
- Kaggle
| Feature | Description |
|---|---|
| Name | en_extract_definitions |
| Version | 0.0.1 |
| spaCy | >=3.7.5,<3.8.0 |
| Default Pipeline | tok2vec, span_finder |
| Components | tok2vec, span_finder |
| Vectors | 514157 keys, 514157 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Accuracy
| Type | Score |
|---|---|
SPANS_SC_F |
67.80 |
SPANS_SC_P |
83.33 |
SPANS_SC_R |
57.14 |
TOK2VEC_LOSS |
543.30 |
SPAN_FINDER_LOSS |
7154.03 |
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