| from transformers import pipeline | |
| # Load the model and tokenizer | |
| # Model: https://huggingface.co/OpenMed/OpenMed-NER-GenomeDetect-BigMed-278M | |
| model_name = "OpenMed/OpenMed-NER-GenomeDetect-BigMed-278M" | |
| # Create a pipeline | |
| medical_ner_pipeline = pipeline( | |
| model=model_name, | |
| aggregation_strategy="simple" | |
| ) | |
| # Example usage | |
| text = "The EGFR gene mutation was identified in lung cancer patients." | |
| entities = medical_ner_pipeline(text) | |
| print(entities) | |
| token = entities[0] | |
| print(text[token["start"] : token["end"]]) | |