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BiliSakura
/
JiT-diffusers

Unconditional Image Generation
Diffusers
Safetensors
English
jit
image-generation
class-conditional
Model card Files Files and versions
xet
Community

Instructions to use BiliSakura/JiT-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use BiliSakura/JiT-diffusers with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("BiliSakura/JiT-diffusers", 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
JiT-diffusers
12.4 GB
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  • 1 contributor
History: 46 commits
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BiliSakura
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  • JiT-B-16
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  • JiT-B-32
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  • JiT-H-16
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  • JiT-H-32
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  • JiT-L-16
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  • JiT-L-32
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  • .gitattributes
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  • README.md
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  • demo_inference.py
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