Instructions to use cgldo/diffusionclone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cgldo/diffusionclone with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cgldo/diffusionclone", 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:
- ae5f661fb3296b73341e3a8a22df2bf4f0949484c5d3a34e9970b65250155e07
- Size of remote file:
- 3.46 GB
- SHA256:
- 33898360ff5abe5e3c51667a5a7d2fd41238de486cd797d2f70fbe45e1a1c310
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