Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
disease-entity-recognition
medical-diagnosis
ncbi
pathology
disease
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Pathology-XLarge-770M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Pathology-XLarge-770M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Pathology-XLarge-770M") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-ZeroShot-NER-Pathology-XLarge-770M
bdbe0d7 verified - Xet hash:
- 99995d2a02f108aabfcc8be2476ee1ef6cb15fa4cd65d3c85129ffcb82937ced
- Size of remote file:
- 16.4 MB
- SHA256:
- d38487ece0ffe3a7bc6650010a9c44d2f79abc3fdbe6415a13f83c151d39cc19
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