Instructions to use udg/anili with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use udg/anili with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("udg/anili", 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:
- 9efe9e7a156bb9842e2ae7b6fa44bd4bb2a74fda899d326ac1d60ea6d79c69b6
- Size of remote file:
- 335 MB
- SHA256:
- 4e13f6e8d3e4ab99c48484fc022630da8e4415964ee5b21a0fca7f95e570a699
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