Instructions to use jhliu/ClinicalNoteBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhliu/ClinicalNoteBERT-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jhliu/ClinicalNoteBERT-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jhliu/ClinicalNoteBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/jhliu/ClinicalNoteBERT-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jhliu/ClinicalNoteBERT-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jhliu/ClinicalNoteBERT-base/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 358d68f4d0f06a5b1d1940270835f3e3edc79390506cbb45a176455d5b15b90c
- Size of remote file:
- 438 MB
- SHA256:
- 2189033b8e33f1567a16ea8022c8c51b43ad9ba866f754ee9cc9409ca1c444be
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