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mit-han-lab
/
svdq-int4-flux.1-depth-dev

Image-to-Image
Diffusers
English
SVDQuant
FLUX.1-Depth-dev
FLUX.1
Diffusion
Quantization
ICLR2025
Model card Files Files and versions
xet
Community
1

Instructions to use mit-han-lab/svdq-int4-flux.1-depth-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use mit-han-lab/svdq-int4-flux.1-depth-dev with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    from diffusers.utils import load_image
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("mit-han-lab/svdq-int4-flux.1-depth-dev", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Turn this cat into a dog"
    input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
    
    image = pipe(image=input_image, prompt=prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
svdq-int4-flux.1-depth-dev
6.77 GB
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  • 1 contributor
History: 17 commits
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Lmxyy
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