Instructions to use camenduru/DemoFusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use camenduru/DemoFusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("camenduru/DemoFusion", 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:
- fca1c354e61ac2bc198b6ea252e04494bb3b66e1fbba757da8627adf8b5fbc9e
- Size of remote file:
- 167 MB
- SHA256:
- 0c800edef1821ae601e7fde7497203f6321d2ca532beddf03c745835d021d5c9
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