Instructions to use nguoidoncui/Controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nguoidoncui/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("nguoidoncui/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:
- ff27b9781af4115fda3a58917d90358fae691bf9675e2f99baa8a63826730e14
- Size of remote file:
- 1.45 GB
- SHA256:
- 657f632c35176c467e71c471b55b1a0e94ae1a49d739e1b705624f454e638e1d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.