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-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-Chemical-Base-220M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Chemical-Base-220M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8895a9ba7f484a821d882f1b2368e13dd99493a8d98314bd6295f4d0cf740950
- Size of remote file:
- 1.21 GB
- SHA256:
- 04cb7c7fe97052f5436a14d813e38e5f72719f4460b13c47b9f7578426be3a5b
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