Instructions to use jhliu/ClinicalNoteBERT-base-simcse_segment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhliu/ClinicalNoteBERT-base-simcse_segment with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jhliu/ClinicalNoteBERT-base-simcse_segment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jhliu/ClinicalNoteBERT-base-simcse_segment: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/jhliu/ClinicalNoteBERT-base-simcse_segment/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jhliu/ClinicalNoteBERT-base-simcse_segment/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jhliu/ClinicalNoteBERT-base-simcse_segment/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- ab93dc2b26391704f61c65c9ea90e4873d1b59684434c5822bc00133b2c1568b
- Size of remote file:
- 440 MB
- SHA256:
- 91f438ce8ec89c8b93a054136d6fd162636423791a5b99983771c5e0055cab77
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