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XonarLabs
/
OLOID_Framework

Text-to-Image
Diffusers
English
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lora
template:diffusion-lora
flux
flux.1-dev
automotive-design
industrial-design
design
agent-friendly
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xet
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Instructions to use XonarLabs/OLOID_Framework with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use XonarLabs/OLOID_Framework 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("XonarLabs/OLOID_Framework")
    
    prompt = "xonar_ext_SUV_rough, A professional studio photography of a SUV, silver metallic gloss paint, 8k resolution, cinematic lighting, dark grey studio background."
    image = pipe(prompt).images[0]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
  • DiffusionBee
OLOID_Framework
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  • 1 contributor
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