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Docty
/
dreambooth-chipped-coating

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 Docty/dreambooth-chipped-coating with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use Docty/dreambooth-chipped-coating with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("Docty/dreambooth-chipped-coating", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Create a container whose entire surface is sksks coated with a color but a has a sksks wear off coating, sksks tear off coating, sksks chipped off coating or sksks peeled off coating exposing the bare uncovered metallic uncoated, sksks chip peeling, rusted, sksks surfaces, sksks wear, cinematic view, realistic"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Draw Things
  • DiffusionBee
dreambooth-chipped-coating / vae
335 MB
Ctrl+K
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  • 1 contributor
History: 1 commit
Docty's picture
Docty
End of training
2245a00 verified about 1 year ago
  • config.json
    909 Bytes
    End of training about 1 year ago
  • diffusion_pytorch_model.safetensors
    335 MB
    xet
    End of training about 1 year ago