Token Classification
Transformers
Safetensors
English
bert
named-entity-recognition
biomedical-nlp
disease-entity-recognition
medical-diagnosis
ncbi
pathology
disease
Instructions to use OpenMed/OpenMed-NER-PathologyDetect-BioMed-335M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-PathologyDetect-BioMed-335M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-PathologyDetect-BioMed-335M")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-BioMed-335M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-PathologyDetect-BioMed-335M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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docs: add citation info to README
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feat: Upload fine-tuned medical NER model OpenMed-NER-PathologyDetect-BioMed-335M
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initial commit
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