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facebook
/
dinov2-large

Image Feature Extraction
Transformers
PyTorch
Safetensors
dinov2
dino
vision
Model card Files Files and versions
xet
Community
7

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

  • Libraries
  • Transformers

    How to use facebook/dinov2-large with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-feature-extraction", model="facebook/dinov2-large")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModel
    
    processor = AutoImageProcessor.from_pretrained("facebook/dinov2-large")
    model = AutoModel.from_pretrained("facebook/dinov2-large")
  • Notebooks
  • Google Colab
  • Kaggle
dinov2-large
2.44 GB
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  • 3 contributors
History: 8 commits
nielsr's picture
nielsr HF Staff
Update license
47b73ee over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    3.03 kB
    Update license over 2 years ago
  • config.json
    549 Bytes
    Upload model almost 3 years ago
  • model.safetensors
    1.22 GB
    xet
    Upload safetensors version (#3) over 2 years ago
  • 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?

    1.22 GB
    xet
    Upload model almost 3 years ago