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ondame
/
image-classifier

Image Classification
Transformers
ONNX
English
multi-head-classification
room-classification
dinov2
computer-vision
scene-classification
Model card Files Files and versions
xet
Community

Instructions to use ondame/image-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ondame/image-classifier with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="ondame/image-classifier")
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("ondame/image-classifier", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
image-classifier
2.43 GB
Ctrl+K
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  • 2 contributors
History: 3 commits
justin-onda's picture
justin-onda
Upload 4 files
0812af4 verified 11 months ago
  • .gitattributes
    1.52 kB
    initial commit 11 months ago
  • README.md
    63 Bytes
    Update README.md 11 months ago
  • image_classifier_model_0.2.onnx
    1.21 GB
    xet
    Upload 4 files 11 months ago
  • image_classifier_model_0.2.pth

    Detected Pickle imports (6)

    • "collections.OrderedDict",
    • "numpy._core.multiarray.scalar",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage",
    • "numpy.dtype",
    • "_codecs.encode"

    How to fix it?

    1.21 GB
    xet
    Upload 4 files 11 months ago
  • image_classifier_model_0.2_inference_example.py
    4.18 kB
    Upload 4 files 11 months ago
  • image_classifier_model_0.2_model_info.json
    2.33 kB
    Upload 4 files 11 months ago