Instructions to use fusing/cifar10-ddpmpp-deep-vp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/cifar10-ddpmpp-deep-vp with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/cifar10-ddpmpp-deep-vp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2647848e5ba2107bf2be3a178e6dc668edb5d5a39dcb3943ad21bbbf030ff813
- Size of remote file:
- 427 MB
- SHA256:
- 4030d46de2576bd20ad45d52e3262bae570eafa0384ddd99baf8f5e4a514a95a
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