Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
species-recognition
taxonomy
organism-identification
biology
species
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Species-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-Species-Medium-209M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Species-Medium-209M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5c7dd47e9c7bcda63b61758e0d518a52f1e5db7de676392b46debe68535132f
- Size of remote file:
- 781 MB
- SHA256:
- db4e410b49566af42f5142ae3bffd571f3b004f9208434ca89cc2067d33d2d7d
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