Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
disease-entity-recognition
medical-diagnosis
ncbi
pathology
disease
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Pathology-XLarge-770M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Pathology-XLarge-770M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Pathology-XLarge-770M") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-ZeroShot-NER-Pathology-XLarge-770M
bdbe0d7 verified | { | |
| "eval_loss": 72.819580078125, | |
| "seqeval_accuracy": 0.9755700325732899, | |
| "seqeval_f1": 0.8872104733131924, | |
| "seqeval_precision": 0.8586744639376218, | |
| "seqeval_recall": 0.9177083333333333 | |
| } |