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kandinsky-community
/
kandinsky-2-2-controlnet-depth

Text-to-Image
Diffusers
KandinskyV22ControlnetPipeline
kandinsky
Model card Files Files and versions
xet
Community
7

Instructions to use kandinsky-community/kandinsky-2-2-controlnet-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use kandinsky-community/kandinsky-2-2-controlnet-depth with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-controlnet-depth", 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
kandinsky-2-2-controlnet-depth
5.29 GB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 16 commits
patrickvonplaten's picture
patrickvonplaten
Update README.md
4ecd717 over 2 years ago
  • movq
    vae-to-movq (#1) almost 3 years ago
  • scheduler
    Update scheduler/scheduler_config.json almost 3 years ago
  • unet
    Upload unet/diffusion_pytorch_model.bin with huggingface_hub almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    9.9 kB
    Update README.md over 2 years ago
  • model_index.json
    260 Bytes
    Update model_index.json (#2) almost 3 years ago