Token Classification
Transformers
Safetensors
English
bert
ner
clinical
medical
healthcare
biomedical
bio-clinicalbert
named-entity-recognition
phi
pii
de-identification
hipaa
ehr
Eval Results (legacy)
Instructions to use genzeonplatform/healthcare-brain-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use genzeonplatform/healthcare-brain-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="genzeonplatform/healthcare-brain-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("genzeonplatform/healthcare-brain-ner") model = AutoModelForTokenClassification.from_pretrained("genzeonplatform/healthcare-brain-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 709eee4b2512b6c58365741ab293512e4b51fdcab25de47b586611d60f59135e
- Size of remote file:
- 431 MB
- SHA256:
- f33aa459a32c0afae05d89d43617ac19d81561e77c4cb843b453ed33dba8916b
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