Instructions to use diffusers/tiny-stable-diffusion-torch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/tiny-stable-diffusion-torch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/tiny-stable-diffusion-torch", 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
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 900d0e21526e7401b54b1b99ebd87ecf29ac3d62afcc1a27ef77da59816b881f
- Size of remote file:
- 284 kB
- SHA256:
- 9f45c03fb8a436f5540c83b3bc6589a18b61e27522b0bf0b3ec665d379da4052
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