Token Classification
Transformers
Safetensors
English
eurobert
named-entity-recognition
biomedical-nlp
disease-entity-recognition
medical-diagnosis
ncbi
pathology
disease
custom_code
Instructions to use OpenMed/OpenMed-NER-PathologyDetect-EuroMed-212M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-PathologyDetect-EuroMed-212M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-PathologyDetect-EuroMed-212M", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-EuroMed-212M", trust_remote_code=True) model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-EuroMed-212M", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "eval_accuracy": 0.9383123497534939, | |
| "eval_f1": 0.6604068857589984, | |
| "eval_loss": 0.4112532436847687, | |
| "eval_precision": 0.659375, | |
| "eval_recall": 0.6614420062695925 | |
| } |