Instructions to use fusing/cifar10-ddpmpp-vp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/cifar10-ddpmpp-vp with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/cifar10-ddpmpp-vp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cb39d25a4ff7b471e5163201fa836cb4a285e53b72d1896b9cc18c38249d013
- Size of remote file:
- 247 MB
- SHA256:
- 1efe0a35418321b5d871427d783692092ddb7cc636726325842cd3c6a0160990
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