Instructions to use CyantifiCQ/noisy_butterflied_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CyantifiCQ/noisy_butterflied_diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CyantifiCQ/noisy_butterflied_diffusion", 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:
- a61e1376d752f19fbf9850678e41f6d595448fbbe14868eb7133ed1ea73ec5de
- Size of remote file:
- 74.3 MB
- SHA256:
- 7ed6b47cd975ed0e8232399a08577d6f3a9cee4fd3e49a92f09635e047abf3f0
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