Instructions to use Narsil/tiny-stable-diffusion-torch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Narsil/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("Narsil/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:
- 1d1719319900c79a3864a130a1637c67aa2c0f0d521613cac12c6b7bc87196b9
- Size of remote file:
- 2.65 MB
- SHA256:
- f19a9557bc1fa4a46f048c0d0614f39986cef05e7ba67c77216dee8a1bcfa5dd
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