Instructions to use natolambert/unet-rl-hopper-tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use natolambert/unet-rl-hopper-tmp with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("natolambert/unet-rl-hopper-tmp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download diffusion_model.pt from natolambert/unet-rl-hopper-tmp: direct link, hf CLI and curl.
- Browser
- Download file 14.8 MB
-
https://huggingface.co/natolambert/unet-rl-hopper-tmp/resolve/main/diffusion_model.pt
- Command line
-
hf download hf://natolambert/unet-rl-hopper-tmp/diffusion_model.pt
-
curl -L -o diffusion_model.pt https://huggingface.co/natolambert/unet-rl-hopper-tmp/resolve/main/diffusion_model.pt
14.8 MB
- Xet hash:
- 22e3e9cdcf0bf0dfa07fcadd7738526349a4a5789db16f0b5def19a56010084c
- Size of remote file:
- 14.8 MB
- SHA256:
- 26ce44a2d2585e92755431b9b6d8dce011f2332fc763d45837ab8986b32ab032
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