Token Classification
Transformers
Safetensors
English
modernbert
named-entity-recognition
biomedical-nlp
gene-recognition
protein-recognition
genomics
molecular-biology
gene/protein
Instructions to use OpenMed/OpenMed-NER-GenomeDetect-ModernClinical-149M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-GenomeDetect-ModernClinical-149M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-GenomeDetect-ModernClinical-149M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-GenomeDetect-ModernClinical-149M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-GenomeDetect-ModernClinical-149M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-NER-GenomeDetect-ModernClinical-149M
e291c1a verified | { | |
| "eval_accuracy": 0.9581371369651143, | |
| "eval_f1": 0.8505386160306736, | |
| "eval_loss": 0.3801855146884918, | |
| "eval_precision": 0.8443413325599942, | |
| "eval_recall": 0.8568275456150677 | |
| } |