Instructions to use jhliu/ClinicalNoteBERT-small-simcse_segment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhliu/ClinicalNoteBERT-small-simcse_segment with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jhliu/ClinicalNoteBERT-small-simcse_segment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jhliu/ClinicalNoteBERT-small-simcse_segment: direct link, hf CLI and curl.
- Browser
- Download file 275 MB
-
https://huggingface.co/jhliu/ClinicalNoteBERT-small-simcse_segment/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jhliu/ClinicalNoteBERT-small-simcse_segment/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jhliu/ClinicalNoteBERT-small-simcse_segment/resolve/main/pytorch_model.bin
275 MB
- Xet hash:
- bd4aca0651cb60864f4270c22f1f03b075cd62bd5eafbb964c581aede1d02444
- Size of remote file:
- 275 MB
- SHA256:
- 7175cd3e2af65a882d6c64c98f3222da28b3a9ae730898327f3ab4753922e5d4
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