Token Classification
Transformers
Safetensors
English
modernbert
named-entity-recognition
biomedical-nlp
anatomical-entity-recognition
medical-terminology
anatomy
healthcare
Instructions to use OpenMed/OpenMed-NER-AnatomyDetect-ModernClinical-395M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-AnatomyDetect-ModernClinical-395M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-AnatomyDetect-ModernClinical-395M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-AnatomyDetect-ModernClinical-395M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-AnatomyDetect-ModernClinical-395M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-NER-AnatomyDetect-ModernClinical-395M
2e426bb verified | { | |
| "eval_accuracy": 0.9756047623434989, | |
| "eval_f1": 0.8740219979589523, | |
| "eval_loss": 0.3481484353542328, | |
| "eval_precision": 0.8779043280182233, | |
| "eval_recall": 0.8701738541431474 | |
| } |