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rcannizzaro
/
image_to_one_hot_causal_factor_vae_dsprites

Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Diffusers

    How to use rcannizzaro/image_to_one_hot_causal_factor_vae_dsprites with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("rcannizzaro/image_to_one_hot_causal_factor_vae_dsprites", 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 Settings
  • Draw Things
  • DiffusionBee
image_to_one_hot_causal_factor_vae_dsprites
1.07 GB
Ctrl+K
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  • 1 contributor
History: 59 commits
rcannizzaro's picture
rcannizzaro
End of training
971163b verified almost 2 years ago
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  • .gitattributes
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  • README.md
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  • config.json
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  • diffusion_pytorch_model.safetensors
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    xet
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