Instructions to use AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation", 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:
- b09646c34545860940088e32a4ff204d239076cfd5e9892ffebb689829c579ac
- Size of remote file:
- 71.5 MB
- SHA256:
- 3c68204f024d3c6cbea29157a1766ca3d4295ca163742e872b8037931b213312
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