Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
protein-interactions
molecular-biology
biochemistry
systems-biology
protein
protein_complex
protein_family
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Protein-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-Protein-Multi-209M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Protein-Multi-209M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82da8a14c8a8cc256ac6e8714db8a52d5d0d7bd872748203f700d24137b8c8f1
- Size of remote file:
- 1.16 GB
- SHA256:
- ac1c3cd964010bdfc32a54354cc87ce98bb7d79b5d58627575dcc195f5a79134
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