Instructions to use jdp8/Stable-Diffusion-3.5-Small-Preview1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jdp8/Stable-Diffusion-3.5-Small-Preview1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jdp8/Stable-Diffusion-3.5-Small-Preview1", 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:
- ecd1f93336b2dd813e7cd8fbf30e32671538e64ee91788962638a2790f43dde2
- Size of remote file:
- 247 MB
- SHA256:
- b4ddf499861727e83713b525ba1e087202f248a7ebb2268b04d1de09de5b67c2
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