Instructions to use fusing/cifar10-ncsnpp-ve with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/cifar10-ncsnpp-ve with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/cifar10-ncsnpp-ve", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d64f3d649fd8325053173bc2f7af97cb0b5a609f5c47a79b565ac659974c8fdd
- Size of remote file:
- 251 MB
- SHA256:
- aaeed0dba247933d0c275f5fbbbf233a51e6089d0f72bc6f3da9cf3943d1e2a4
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