Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
gene-recognition
genetics
genomics
molecular-biology
gene
genetic_variant
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Genomic-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-Genomic-Multi-209M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Genomic-Multi-209M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 605432159e640410f8a450ea9b0821bc3d139197f172c6ff3c3fb5fcf54a85b2
- Size of remote file:
- 1.16 GB
- SHA256:
- 6c406fb9c799aab30a09f7b0318223e7024d038de179d24499500ec36afe50a8
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