Token Classification
Transformers
Safetensors
English
roberta
named-entity-recognition
biomedical-nlp
anatomical-entity-recognition
medical-terminology
anatomy
healthcare
Instructions to use OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 131 Bytes
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