Token Classification
Transformers
Safetensors
English
modernbert
named-entity-recognition
biomedical-nlp
disease-entity-recognition
medical-diagnosis
pathology
biocuration
disease
Instructions to use OpenMed/OpenMed-NER-DiseaseDetect-ModernClinical-149M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-DiseaseDetect-ModernClinical-149M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-DiseaseDetect-ModernClinical-149M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-DiseaseDetect-ModernClinical-149M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-DiseaseDetect-ModernClinical-149M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-NER-DiseaseDetect-ModernClinical-149M
aa95624 verified | { | |
| "eval_accuracy": 0.9729784425868896, | |
| "eval_f1": 0.8794118990000458, | |
| "eval_loss": 0.3532900810241699, | |
| "eval_precision": 0.8666306695464363, | |
| "eval_recall": 0.8925757716192418 | |
| } |