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chris32
/
living-spaces-classification

Image Classification
Transformers
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use chris32/living-spaces-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use chris32/living-spaces-classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="chris32/living-spaces-classification")
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModelForImageClassification
    
    processor = AutoImageProcessor.from_pretrained("chris32/living-spaces-classification")
    model = AutoModelForImageClassification.from_pretrained("chris32/living-spaces-classification", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
living-spaces-classification / images
146 kB
Ctrl+K
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  • 1 contributor
History: 1 commit
chris32's picture
chris32
commit files to HF hub
4bf8101 almost 3 years ago
  • Exterior.jpg
    11.6 kB
    xet
    commit files to HF hub almost 3 years ago
  • Interior.jpg
    10.2 kB
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    commit files to HF hub almost 3 years ago
  • bathroom.jpg
    11.1 kB
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    commit files to HF hub almost 3 years ago
  • bedroom.jpg
    11.5 kB
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    commit files to HF hub almost 3 years ago
  • closets.JPEG
    67.5 kB
    xet
    commit files to HF hub almost 3 years ago
  • dining_room.jpg
    7.34 kB
    xet
    commit files to HF hub almost 3 years ago
  • kitchen.jpg
    8.5 kB
    xet
    commit files to HF hub almost 3 years ago
  • living_room.jpg
    12 kB
    xet
    commit files to HF hub almost 3 years ago
  • others
    6.15 kB
    xet
    commit files to HF hub almost 3 years ago