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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e413584523d10ee684cf8ccc0a7f402460d52f9e38c9787cd936832f15eb3e3e
- Size of remote file:
- 5.74 MB
- SHA256:
- 3cc00c21100c2b750b23c0a325ed11accec91c66d49d4668c295fc5b3e7a7661
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