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-Tiny-60M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Protein-Tiny-60M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Protein-Tiny-60M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3b1394001e1fb65e1323b67164a5f1ca4b05ceb4d4964f02b9c5aaa53e31b2a
- Size of remote file:
- 689 MB
- SHA256:
- 8a25ff1b49b7ade71efe2921fb476241c545859ea7a6850359cdb2707798746d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.