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:
- 95e14c5f52aece72d48adf0e49b5893fbea57cafc9f1835458db34495eb5f64b
- Size of remote file:
- 1.73 GB
- SHA256:
- 5a9377eed7dfd84a3522929555a575b97110ccd8c4a0e7270ac7d31cad1e28dd
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