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dataautogpt3
/
FluxteusV1

Text-to-Image
Diffusers
flux
flux-diffusers
Model card Files Files and versions
xet
Community
3

Instructions to use dataautogpt3/FluxteusV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use dataautogpt3/FluxteusV1 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("dataautogpt3/FluxteusV1", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image)  An Oscar winning movie for Best Cinematography a woman in a kimono  standing on a subway train in Japan Kodak Motion Picture Film Style,  shallow depth of field, vignette, highly detailed, high budget, bokeh,  cinemascope, moody, epic, gorgeous, film grain, grainy\n"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
  • DiffusionBee
FluxteusV1 / assets
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dataautogpt3
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