Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
gene-recognition
protein-recognition
genomics
molecular-biology
gene
protein
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Genome-Multi-209M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Genome-Multi-209M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Genome-Multi-209M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba3cb75d3115d65b530f346384df423dd6d2877942eddbdbfcb1debe7e443f78
- Size of remote file:
- 1.16 GB
- SHA256:
- 565b976fc7da9ae38867606593cd988969cc8e322227a415009f5250d87df0e1
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