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ShadeEngine
/
SD_kirby_dreambooth

Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use ShadeEngine/SD_kirby_dreambooth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use ShadeEngine/SD_kirby_dreambooth with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("ShadeEngine/SD_kirby_dreambooth", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "a photo of kirby"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Draw Things
  • DiffusionBee
SD_kirby_dreambooth / diffusers /docs /source /ko /training
116 kB
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  • 1 contributor
History: 1 commit
ShadeEngine's picture
ShadeEngine
End of training
4ac8f3e verified almost 2 years ago
  • adapt_a_model.md
    3.22 kB
    End of training almost 2 years ago
  • controlnet.md
    14.9 kB
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  • create_dataset.md
    4.87 kB
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  • custom_diffusion.md
    12.5 kB
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  • distributed_inference.md
    4.4 kB
    End of training almost 2 years ago
  • dreambooth.md
    20.3 kB
    End of training almost 2 years ago
  • instructpix2pix.md
    9.92 kB
    End of training almost 2 years ago
  • lora.md
    7.58 kB
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  • overview.md
    7.43 kB
    End of training almost 2 years ago
  • text2image.md
    10.3 kB
    End of training almost 2 years ago
  • text_inversion.md
    14.7 kB
    End of training almost 2 years ago
  • unconditional_training.md
    5.47 kB
    End of training almost 2 years ago