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-SnowMed-568M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-DiseaseDetect-SnowMed-568M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-DiseaseDetect-SnowMed-568M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-DiseaseDetect-SnowMed-568M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-DiseaseDetect-SnowMed-568M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "eval_accuracy": 0.975231819522477, | |
| "eval_f1": 0.8737162251509675, | |
| "eval_loss": 0.3463221490383148, | |
| "eval_precision": 0.8619759958253609, | |
| "eval_recall": 0.885780677451068 | |
| } |