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
| { | |
| "eval_loss": 39.223148345947266, | |
| "seqeval_accuracy": 0.9977424837990014, | |
| "seqeval_f1": 0.9750692520775623, | |
| "seqeval_precision": 0.9676975945017182, | |
| "seqeval_recall": 0.9825540823447313 | |
| } |