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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 /en /api /pipelines /stable_diffusion
75.6 kB
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  • 1 contributor
History: 1 commit
ShadeEngine's picture
ShadeEngine
End of training
4ac8f3e verified almost 2 years ago
  • adapter.md
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  • depth2img.md
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  • gligen.md
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  • image_variation.md
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  • img2img.md
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  • inpaint.md
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  • k_diffusion.md
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  • latent_upscale.md
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  • ldm3d_diffusion.md
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  • overview.md
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  • sdxl_turbo.md
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  • stable_diffusion_2.md
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  • stable_diffusion_3.md
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  • stable_diffusion_safe.md
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  • stable_diffusion_xl.md
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  • svd.md
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  • text2img.md
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  • upscale.md
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