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facebook
/
dinov2-base

Image Feature Extraction
Transformers
PyTorch
Safetensors
dinov2
dino
vision
Model card Files Files and versions
xet
Community
14

Instructions to use facebook/dinov2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use facebook/dinov2-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-feature-extraction", model="facebook/dinov2-base")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModel
    
    processor = AutoImageProcessor.from_pretrained("facebook/dinov2-base")
    model = AutoModel.from_pretrained("facebook/dinov2-base")
  • Notebooks
  • Google Colab
  • Kaggle
dinov2-base
1.04 GB
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  • 3 contributors
History: 11 commits
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GooKSL
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f2604a6 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    3.03 kB
    Update README.md almost 3 years ago
  • config.json
    886 Bytes
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  • flax_model.msgpack
    346 MB
    xet
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  • model.safetensors
    346 MB
    xet
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  • preprocessor_config.json
    436 Bytes
    Upload processor almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict",
    • "torch.FloatStorage"

    What is a pickle import?

    346 MB
    xet
    Upload model almost 3 years ago