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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 /examples /controlnet
179 kB
Ctrl+K
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  • 1 contributor
History: 1 commit
ShadeEngine's picture
ShadeEngine
End of training
4ac8f3e verified almost 2 years ago
  • README.md
    19.4 kB
    End of training almost 2 years ago
  • README_sdxl.md
    5.56 kB
    End of training almost 2 years ago
  • requirements.txt
    78 Bytes
    End of training almost 2 years ago
  • requirements_flax.txt
    83 Bytes
    End of training almost 2 years ago
  • requirements_sdxl.txt
    91 Bytes
    End of training almost 2 years ago
  • test_controlnet.py
    4.47 kB
    End of training almost 2 years ago
  • train_controlnet.py
    48 kB
    End of training almost 2 years ago
  • train_controlnet_flax.py
    45.2 kB
    End of training almost 2 years ago
  • train_controlnet_sdxl.py
    55.9 kB
    End of training almost 2 years ago