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Motas
/
Flux_Glitch_Style

Text-to-Image
Diffusers
stable-diffusion
lora
template:sd-lora
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Diffusers

    How to use Motas/Flux_Glitch_Style with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
    pipe.load_lora_weights("Motas/Flux_Glitch_Style")
    
    prompt = "\"Abstract nun figure with a white robe, faceless with a vertical cascading digital distortion where the face should be. The distortion is composed of vibrant red and orange pixels, resembling digital noise, set against a dark background. The figure has hands in a praying position, blending a religious theme with glitch art aesthetics.\""
    image = pipe(prompt).images[0]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
  • DiffusionBee
Flux_Glitch_Style
78.2 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
Motas's picture
Motas
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  • Glitch.safetensors
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  • README.md
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