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-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-Pathology-Base-220M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Pathology-Base-220M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8245f5e6d30e22fd4e96fe26a1fa215aeb17884cf68a8388506e0bdf87caacb9
- Size of remote file:
- 1.21 GB
- SHA256:
- 90f266db610ab87b8bc1452ed63933c9f72d34b89489cdf3f7ae516bf6b29385
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