Token Classification
Transformers
Safetensors
English
xlm-roberta
named-entity-recognition
biomedical-nlp
disease-entity-recognition
medical-diagnosis
pathology
biocuration
disease
Instructions to use OpenMed/OpenMed-NER-DiseaseDetect-BigMed-278M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-DiseaseDetect-BigMed-278M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-DiseaseDetect-BigMed-278M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-DiseaseDetect-BigMed-278M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-DiseaseDetect-BigMed-278M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "eval_accuracy": 0.974102396247725, | |
| "eval_f1": 0.8695957512180135, | |
| "eval_loss": 0.3515494167804718, | |
| "eval_precision": 0.8544074521304122, | |
| "eval_recall": 0.8853338099919564 | |
| } |