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BiliSakura
/
ZoomLDM-naip

Image-to-Image
Diffusers
Safetensors
ZoomLDMPipeline
zoomldm
remote-sensing
naip
latent-diffusion
custom-pipeline
arxiv:2411.16969
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Diffusers

    How to use BiliSakura/ZoomLDM-naip 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("BiliSakura/ZoomLDM-naip", 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
ZoomLDM-naip
1.98 GB
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  • 1 contributor
History: 4 commits
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BiliSakura
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  • conditioning_encoder
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  • demo_data
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  • demo_images
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  • ldm
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  • scheduler
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  • unet
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  • vae
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  • .gitattributes
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  • README.md
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  • model_index.json
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  • pipeline_zoomldm.py
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  • run_demo_inference.py
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