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-Small-166M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Pathology-Small-166M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Pathology-Small-166M") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-ZeroShot-NER-Pathology-Small-166M
de3f0c6 verified - Xet hash:
- cbb8f21de090a120b95d6fa992efc6ca5f58cc240ab72cdaabf50a299b8a679b
- Size of remote file:
- 611 MB
- SHA256:
- c899b9021738c83d0215b753eb7d26828adefd9c9f4716c1690a00911c1079a9
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