Token Classification
Transformers
Safetensors
English
modernbert
named-entity-recognition
biomedical-nlp
protein-recognition
gene-recognition
molecular-biology
genomics
dna
rna
cell_line
cell_type
protein
Instructions to use OpenMed/OpenMed-NER-DNADetect-ModernClinical-395M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-DNADetect-ModernClinical-395M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-DNADetect-ModernClinical-395M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-DNADetect-ModernClinical-395M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-DNADetect-ModernClinical-395M") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-NER-DNADetect-ModernClinical-395M
9a9c6ea verified | { | |
| "eval_accuracy": 0.9224012869680125, | |
| "eval_f1": 0.7809302816158633, | |
| "eval_loss": 0.717052161693573, | |
| "eval_precision": 0.740725919404538, | |
| "eval_recall": 0.8257494646680942 | |
| } |