Instructions to use valhalla/controlnet-pix2pix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use valhalla/controlnet-pix2pix with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("valhalla/controlnet-pix2pix", torch_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:
- 7b3d64b19924d0ff3cf3ea76a2d5b9e6abc411c662b3b18f330bc48f12b37bc8
- Size of remote file:
- 2.5 GB
- SHA256:
- fb005838614a7dc0892fb51dd8e73795f8fb8fa931a840c42a3c73c869e15974
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.