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-Medium-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-Medium-209M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Genome-Medium-209M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd8191dd951405173d5d4751df4c689a0c6d8f9877c5c33803758f47c44b6db0
- Size of remote file:
- 781 MB
- SHA256:
- a11a7d7c3bda4d49fdfd0e191b06451486224af16612fd437ce573691de7ae69
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.