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:
- 98f8208568ebe493e2c55aab7eb6715dd03b302d09936363101dcaff877f4c49
- Size of remote file:
- 1.39 GB
- SHA256:
- c4ba596d8c78b5509aafd523f619e13aa129ae1a886a1e92766d7cddd9706f3c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.