Instructions to use jhliu/ClinicalNoteBERT-base-note_only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhliu/ClinicalNoteBERT-base-note_only with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jhliu/ClinicalNoteBERT-base-note_only", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jhliu/ClinicalNoteBERT-base-note_only: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/jhliu/ClinicalNoteBERT-base-note_only/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jhliu/ClinicalNoteBERT-base-note_only/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jhliu/ClinicalNoteBERT-base-note_only/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- d21b54c83cc1b7c793d17b65847f87a1d78116a9bc12cc61ad649f8c5acf847f
- Size of remote file:
- 438 MB
- SHA256:
- 18c6bb06b8a690319a112f167eb7bdd61916059433984bcb584d898842d56cf9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.