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LibreYOLO
/
LibreDINOv3vith16plus

Image Feature Extraction
Transformers
Safetensors
dinov3_vit
dinov3
vision
libreyolo
Model card Files Files and versions
xet
Community

Instructions to use LibreYOLO/LibreDINOv3vith16plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use LibreYOLO/LibreDINOv3vith16plus with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-feature-extraction", model="LibreYOLO/LibreDINOv3vith16plus")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoImageProcessor, AutoModel
    
    processor = AutoImageProcessor.from_pretrained("LibreYOLO/LibreDINOv3vith16plus")
    model = AutoModel.from_pretrained("LibreYOLO/LibreDINOv3vith16plus", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
LibreDINOv3vith16plus
1.68 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Xuban's picture
Xuban
Mirror Meta's DINOv3 ViT-H+/16 (LVD-1689M) in bfloat16 under the DINOv3 License
e849a34 verified 2 days ago
  • .gitattributes
    1.52 kB
    initial commit 2 days ago
  • LICENSE
    7.5 kB
    Mirror Meta's DINOv3 ViT-H+/16 (LVD-1689M) in bfloat16 under the DINOv3 License 2 days ago
  • NOTICE
    530 Bytes
    Mirror Meta's DINOv3 ViT-H+/16 (LVD-1689M) in bfloat16 under the DINOv3 License 2 days ago
  • README.md
    3.92 kB
    Mirror Meta's DINOv3 ViT-H+/16 (LVD-1689M) in bfloat16 under the DINOv3 License 2 days ago
  • config.json
    745 Bytes
    Mirror Meta's DINOv3 ViT-H+/16 (LVD-1689M) in bfloat16 under the DINOv3 License 2 days ago
  • model.safetensors
    1.68 GB
    xet
    Mirror Meta's DINOv3 ViT-H+/16 (LVD-1689M) in bfloat16 under the DINOv3 License 2 days ago
  • preprocessor_config.json
    585 Bytes
    Mirror Meta's DINOv3 ViT-H+/16 (LVD-1689M) in bfloat16 under the DINOv3 License 2 days ago