Instructions to use jhliu/ClinicalNoteBERT-tiny-simcse_sentence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhliu/ClinicalNoteBERT-tiny-simcse_sentence with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jhliu/ClinicalNoteBERT-tiny-simcse_sentence", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jhliu/ClinicalNoteBERT-tiny-simcse_sentence: direct link, hf CLI and curl.
- Browser
- Download file 59.8 MB
-
https://huggingface.co/jhliu/ClinicalNoteBERT-tiny-simcse_sentence/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jhliu/ClinicalNoteBERT-tiny-simcse_sentence/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jhliu/ClinicalNoteBERT-tiny-simcse_sentence/resolve/main/pytorch_model.bin
59.8 MB
- Xet hash:
- 5a969b12f0f2148e3e768ef8eb7c6ee07f58e2fe8cae964429b91401c06b190d
- Size of remote file:
- 59.8 MB
- SHA256:
- 58663b706eb70e222dc2bccd166fa304a6a8798a9cc881e3e895f616b5dcee8f
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