Instructions to use alimama-creative/SD3-Controlnet-Inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alimama-creative/SD3-Controlnet-Inpainting with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("alimama-creative/SD3-Controlnet-Inpainting", 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
Input type (torch.cuda.HalfTensor) and weight type (torch.HalfTensor) should be the same
#17
by aniket2025 - opened
While using the same code on my already available control image and control mask, it shows the error
Also, i would like to know control image is the image we add as reference, control mask is the mask of the actual source image. Then where to supply the actual image? In previous version, we can supply the source image, source image mask and the control image.