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-Base-220M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Disease-Base-220M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Disease-Base-220M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93c5260c19a0a8c7f4b0bf896619a90d7c60d29ada5483056c47355726937e3d
- Size of remote file:
- 1.21 GB
- SHA256:
- 7a30f4f9e4da6da47c6c7748391a66e7b8b09e2ce47b83be269fff771c7d6735
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