Instructions to use SaitoHoujou/Finetuned-ControlNet_for_Diffusion-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SaitoHoujou/Finetuned-ControlNet_for_Diffusion-Model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SaitoHoujou/Finetuned-ControlNet_for_Diffusion-Model", 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:
- 485ce7f5e2157dd3e5074b0dbb5270ce41f96309b4c27fa62ff2c7f05ade1f3a
- Size of remote file:
- 1.45 GB
- SHA256:
- 07c42f307a8f05f593a08049a39432583687f416714674c995545e6733e21e06
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