Instructions to use google/ddpm-cifar10-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use google/ddpm-cifar10-32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("google/ddpm-cifar10-32", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b2314b91bb02c8bb49887684e76320af9935e8b5e60a469a01139f03c618afb
- Size of remote file:
- 143 MB
- SHA256:
- ac3416a548879738893e935b42cab9119f51745b62bec4b6d8375e4d86e98ea4
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