Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
disease-entity-recognition
medical-diagnosis
pathology
biocuration
disease
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Disease-Tiny-60M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Disease-Tiny-60M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Disease-Tiny-60M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0e808ea906f00c59d0bf5864f6a6594120a2b3997dd0ba45002a43e5e16c1b7
- Size of remote file:
- 16.3 MB
- SHA256:
- c23b87e1609c72116a5aea222f983df99723cb2afa554d9d137f289840c3097b
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