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-XLarge-770M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Pharma-XLarge-770M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Pharma-XLarge-770M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a7a6f8b296eee91b3e2234a8a3c3649c61d41e35e897afb8f5c394951a31eb2
- Size of remote file:
- 2.43 GB
- SHA256:
- 95d9bd8e7eaffab65eb0304d4d1b0b6bc102486b6522bca7260fb97c3d0ea0fe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.