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-Base-220M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-DNA-Base-220M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-DNA-Base-220M") - Notebooks
- Google Colab
- Kaggle
| { | |
| "eval_loss": 299.10894775390625, | |
| "seqeval_accuracy": 0.9419684468533158, | |
| "seqeval_f1": 0.7907479463899698, | |
| "seqeval_precision": 0.7433448486080065, | |
| "seqeval_recall": 0.8446086354190718 | |
| } |