Text Classification
Transformers
PyTorch
English
medical
clinical-notes
cardiac-arrest
ohca
biomedical-nlp
pubmedbert
Instructions to use monajm36/ohca-classifier-v11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monajm36/ohca-classifier-v11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="monajm36/ohca-classifier-v11")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("monajm36/ohca-classifier-v11", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c87eeb316bf4ad8a0fbd38d123dd500c6d1752f1773107c18c14d69b42f982fe
- Size of remote file:
- 440 MB
- SHA256:
- 2d52722b9ceda19d11eaba92fe0384c4d9a0520cbf962b98605f50289407bf57
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