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:
- 008bee3f15ad4fdee68e1b6edafa24eab7d6922a6f83ca36750b216cd07e7a22
- Size of remote file:
- 284 kB
- SHA256:
- fcd9bf150bd5fbf04e4a4ba5c141a1a275a2e8d1903a47e82bf764d5dfedbd3b
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