Instructions to use 24aittl/controlnet-prodigy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 24aittl/controlnet-prodigy with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("24aittl/controlnet-prodigy", 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
- Xet hash:
- 9856c8be03e0d489e45f01ae908f2386fc21ac2cedd64bbdf6844069f148f1a5
- Size of remote file:
- 5.39 GB
- SHA256:
- 347138cac5fdb69b8d2cba45e1148a5dc5827d901762e3eda4d3609204329235
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