Instructions to use GleghornLab/CAMP_nat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GleghornLab/CAMP_nat with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import CAMP model = CAMP.from_pretrained("GleghornLab/CAMP_nat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from GleghornLab/CAMP_nat: direct link, hf CLI and curl.
- Browser
- Download file 1.57 GB
-
https://huggingface.co/GleghornLab/CAMP_nat/resolve/a242827b0cb28be4fa4a00a9fdedd577baf0158d/model.safetensors
- Command line
-
hf download hf://GleghornLab/CAMP_nat@a242827b0cb28be4fa4a00a9fdedd577baf0158d/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/GleghornLab/CAMP_nat/resolve/a242827b0cb28be4fa4a00a9fdedd577baf0158d/model.safetensors
1.57 GB
- Xet hash:
- ea2c0129b6ea3b520f57c8a201b5d63b9151824cd2f9aad08bc42095c0d8d654
- Size of remote file:
- 1.57 GB
- SHA256:
- 7084a6a68b97a2fa017355fb59a5f3c752a7fd057553cc789965b96ad71ef66c
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