Instructions to use jhliu/ClinicalNoteBERT-tiny-simcse_note with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhliu/ClinicalNoteBERT-tiny-simcse_note with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jhliu/ClinicalNoteBERT-tiny-simcse_note", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jhliu/ClinicalNoteBERT-tiny-simcse_note: direct link, hf CLI and curl.
- Browser
- Download file 59.8 MB
-
https://huggingface.co/jhliu/ClinicalNoteBERT-tiny-simcse_note/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jhliu/ClinicalNoteBERT-tiny-simcse_note/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jhliu/ClinicalNoteBERT-tiny-simcse_note/resolve/main/pytorch_model.bin
59.8 MB
- Xet hash:
- 31cb76816da2cfd8d1a98a2f24678dd8114d4ac7d8e32566c1826fe4805aa9b5
- Size of remote file:
- 59.8 MB
- SHA256:
- 8a03d195b8f5efe73fd6fb65534453fe8203fc29fd33117aaf6c62be37cced30
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