Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
chemical-entity-recognition
drug-discovery
pharmacology
chemistry
chemical
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Chemical-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-Chemical-Small-166M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Chemical-Small-166M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15803b5cc3c41011ea5dd6b2a9e243447543c509fdd4ada17f88c773a809784d
- Size of remote file:
- 611 MB
- SHA256:
- c2f6b1dcf41c5970571f10b9d8a9242095a0e842181f79c82f37e18d4720fb73
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