Instructions to use fusing/ffhq_256-ncsnpp-ve with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/ffhq_256-ncsnpp-ve with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/ffhq_256-ncsnpp-ve", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 283338b12aa248471bd58a9f8a30cf98041630cf8fbee943dbd49b1cecbad535
- Size of remote file:
- 263 MB
- SHA256:
- 3ea5dc9ea180483e9c65905ae2e4531ba0101792b30df0bcdfe16f51cc8c0e71
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