Token Classification
Transformers
Safetensors
English
xlm-roberta
named-entity-recognition
biomedical-nlp
disease-entity-recognition
medical-diagnosis
ncbi
pathology
disease
Instructions to use OpenMed/OpenMed-NER-PathologyDetect-SnowMed-568M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-PathologyDetect-SnowMed-568M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-PathologyDetect-SnowMed-568M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-SnowMed-568M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-SnowMed-568M") - Notebooks
- Google Colab
- Kaggle
| { | |
| "eval_accuracy": 0.973078658444879, | |
| "eval_f1": 0.8902522154055896, | |
| "eval_loss": 0.3564680516719818, | |
| "eval_precision": 0.8683510638297872, | |
| "eval_recall": 0.9132867132867133 | |
| } |