Instructions to use timlenardo/own_controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use timlenardo/own_controlnet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("timlenardo/own_controlnet", 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:
- e9d3e33a1932c5b4b462d62f80487cfa5a51bed5ea76272ac925d645480f1ff1
- Size of remote file:
- 1.45 GB
- SHA256:
- 330b191c1b98b89c55f2d371966759e9c703913747df85a00efbe449b018e7d6
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