Instructions to use Compumacy/sdxlturbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Compumacy/sdxlturbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Compumacy/sdxlturbo", 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:
- 03fc18a983c771c0d8858c5e552a51f87c2871cc78c9ac9b3b9b4e24b57d8df2
- Size of remote file:
- 198 MB
- SHA256:
- 558225daaa98ae7e67594d10a1ac3e546c67b12094836f8788036aaba652e159
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.