Instructions to use CameronDugan/PixelDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CameronDugan/PixelDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CameronDugan/PixelDiffusion", 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:
- b3aeeed1fce3acddc7e58e107e48e64184bd8e792f7e571a17b91ac8bc601955
- Size of remote file:
- 23.6 MB
- SHA256:
- f7a92ab8900b2276b90b08fb59f77c72c2b00e4c26f0d7cf0118105c81342e25
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