Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
species-recognition
taxonomy
organism-identification
biodiversity
species
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Organism-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-Organism-Multi-209M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Organism-Multi-209M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da30a42d4fe124f98a38d94787515454a43dd10d9b1a81557a043404b2a44111
- Size of remote file:
- 1.16 GB
- SHA256:
- dc1a81cf90df15a19c568eb9d0167c3725d36cd7f9ca551698922390b08398e3
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