Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
protein-recognition
gene-recognition
molecular-biology
genomics
protein
dna
rna
cell_line
cell_type
Instructions to use OpenMed/OpenMed-ZeroShot-NER-DNA-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-DNA-Medium-209M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-DNA-Medium-209M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a87ae45ea8ab6da56e5a6717863f9c4eb6bc1e8719b7188ecd2e79c20637a8c3
- Size of remote file:
- 781 MB
- SHA256:
- c870437351825f56dbe7192556e3fde66116cd16e5eabecf1567f31083c267c8
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