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
biocuration
chemical
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Pharma-Large-459M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Pharma-Large-459M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Pharma-Large-459M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 323ee57db2da5d8b7396c05025cdbe19308d6c1e0be8daf8aa27e5abca015ac1
- Size of remote file:
- 1.78 GB
- SHA256:
- db92b1fa3411ddcd09e2639462832c5b9108157c4cc27b424eae971d000b7b9c
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