Instructions to use diffusers/controlnet-canny-sdxl-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/controlnet-canny-sdxl-1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/controlnet-canny-sdxl-1.0", 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
- Local Apps
- Draw Things
- DiffusionBee
Why Change VAE?
#25
by marcdemory - opened
What is the purpose of using this VAE instead of the default one on the SDXLControlNet pipeline?
Does it generate better results, improve memory usage, etc.
vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16).to("cuda")
We kept the vae in fp16 during training and iirc there are issues with the standard sdxl vae in fp16. I believe https://huggingface.co/madebyollin/sdxl-vae-fp16-fix has more details
williamberman changed discussion status to closed