Instructions to use dde/aut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dde/aut with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dde/aut", 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:
- 6a2c1e5a2586d7f293c490147e84bda5c28eb2690ea64287ced06135885abe08
- Size of remote file:
- 2.78 GB
- SHA256:
- 8b6dce4c35dc70ba921ff6ab46f35ad372cafa99874debf68275b16aefeca326
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