Token Classification
Transformers
Safetensors
English
bert
named-entity-recognition
biomedical-nlp
disease-entity-recognition
medical-diagnosis
ncbi
pathology
disease
Instructions to use OpenMed/OpenMed-NER-PathologyDetect-BioClinical-108M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-PathologyDetect-BioClinical-108M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-PathologyDetect-BioClinical-108M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-BioClinical-108M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-BioClinical-108M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-NER-PathologyDetect-BioClinical-108M
245859d verified | { | |
| "eval_accuracy": 0.9653787564049301, | |
| "eval_f1": 0.8778450615994989, | |
| "eval_loss": 0.3664607107639313, | |
| "eval_precision": 0.8583095140873827, | |
| "eval_recall": 0.8982905982905983 | |
| } |