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NinjaGoose
/
toyota-celica

Text-to-Image
Diffusers
flux
lora
template:sd-lora
ai-toolkit
Model card Files Files and versions
xet
Community

Instructions to use NinjaGoose/toyota-celica with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use NinjaGoose/toyota-celica 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("NinjaGoose/toyota-celica")
    
    prompt = "A stunning anime-style illustration of a bustling Tokyo auto garage at night, where a sleek black  toyota_celica is undergoing maintenance under the warm glow of overhead shop lights. The garage is filled with energy, with four skilled mechanics in red and white uniforms working meticulously—one carefully refueling the tank, another swapping out a tire with precision, while the others inspect the engine. The air is thick with the hum of tools and the scent of motor oil, with neon kanji signs flickering outside, casting a cool blue glow on the concrete floor. The atmosphere feels alive—an electric blend of high-performance car culture and the dreamy warmth of hand-drawn anime detailing, capturing the heart of Tokyo’s underground tuning scene."
    image = pipe(prompt).images[0]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Draw Things
  • DiffusionBee
toyota-celica
345 MB
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  • 1 contributor
History: 2 commits
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