Instructions to use jhliu/ClinicalNoteBERT-base-note_only-simcse_note with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhliu/ClinicalNoteBERT-base-note_only-simcse_note with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jhliu/ClinicalNoteBERT-base-note_only-simcse_note", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jhliu/ClinicalNoteBERT-base-note_only-simcse_note: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/jhliu/ClinicalNoteBERT-base-note_only-simcse_note/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jhliu/ClinicalNoteBERT-base-note_only-simcse_note/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jhliu/ClinicalNoteBERT-base-note_only-simcse_note/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 5a22cd560c2980de4bbfff0feb3119fff2600b7b2b0783a456678d7cc623ed31
- Size of remote file:
- 440 MB
- SHA256:
- 8ee68f2b7448b12eb2bae88ea2f801de0e20cfe1cf92c5dd58335f813fd07cd1
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