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AImageLab-Zip
/
US_Cond-UNet

Image Segmentation
Transformers
Safetensors
cond_unet
ultrasound
medical-image-segmentation
attention-unet
custom-pipeline
custom_code
Model card Files Files and versions
xet
Community

Instructions to use AImageLab-Zip/US_Cond-UNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AImageLab-Zip/US_Cond-UNet with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-segmentation", model="AImageLab-Zip/US_Cond-UNet", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForImageSegmentation
    model = AutoModelForImageSegmentation.from_pretrained("AImageLab-Zip/US_Cond-UNet", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
US_Cond-UNet
192 MB
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  • 1 contributor
History: 12 commits
Morelli001's picture
Morelli001
Update README.md
f25d73b verified 3 days ago
  • .gitattributes
    1.52 kB
    initial commit 4 days ago
  • README.md
    2.12 kB
    Update README.md 3 days ago
  • config.json
    1.1 kB
    Upload folder using huggingface_hub 4 days ago
  • configuration_cond_unet.py
    1.44 kB
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  • image_processing_cond_unet.py
    3.2 kB
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  • model.safetensors
    191 MB
    xet
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  • modeling_cond_unet.py
    2.42 kB
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  • pipeline.py
    2.22 kB
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  • preprocessor_config.json
    234 Bytes
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  • requirements.txt
    72 Bytes
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  • segm_net.py
    35.7 kB
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  • unet_attn.py
    33.8 kB
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  • unet_base.py
    11.9 kB
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