Token Classification
Transformers
Safetensors
English
modernbert
named-entity-recognition
biomedical-nlp
disease-entity-recognition
medical-diagnosis
ncbi
pathology
disease
Instructions to use OpenMed/OpenMed-NER-PathologyDetect-ModernMed-149M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-PathologyDetect-ModernMed-149M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-PathologyDetect-ModernMed-149M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-ModernMed-149M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-ModernMed-149M") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-NER-PathologyDetect-ModernMed-149M
3b6de8d verified | { | |
| "eval_accuracy": 0.943538096974116, | |
| "eval_f1": 0.7543733525041935, | |
| "eval_loss": 0.40261611342430115, | |
| "eval_precision": 0.757823784304285, | |
| "eval_recall": 0.7509541984732825 | |
| } |