| Feature | Description |
|---|---|
| Name | en_pipeline_ner_model_d |
| Version | 0.0.0 |
| spaCy | >=3.7.2,<3.8.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (4 labels for 1 components)
| Component | Labels |
|---|---|
ner |
allergy_name, cancer, chronic_disease, treatment |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
94.80 |
ENTS_P |
94.71 |
ENTS_R |
94.89 |
TRANSFORMER_LOSS |
406496.45 |
NER_LOSS |
452435.57 |
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Evaluation results
- NER Precisionself-reported0.947
- NER Recallself-reported0.949
- NER F Scoreself-reported0.948
!pip install https://huggingface.co/rame/en_pipeline_ner_model_d/resolve/main/en_pipeline_ner_model_d-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_pipeline_ner_model_d") # Importing as module. import en_pipeline_ner_model_d nlp = en_pipeline_ner_model_d.load()