| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.4.4,<3.5.0 |
| 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
View label scheme (3 labels for 1 components)
| Component | Labels |
|---|---|
ner |
MEDICALCONDITION, MEDICINE, PATHOGEN |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
98.82 |
ENTS_P |
98.44 |
ENTS_R |
99.21 |
TOK2VEC_LOSS |
12068.08 |
NER_LOSS |
27961.10 |
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Evaluation results
- NER Precisionself-reported0.984
- NER Recallself-reported0.992
- NER F Scoreself-reported0.988
!pip install https://huggingface.co/rahulpointer/en_pipeline/resolve/main/en_pipeline-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_pipeline") # Importing as module. import en_pipeline nlp = en_pipeline.load()