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facebook
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vjepa2-vith-fpc64-256

Video Classification
Transformers
Safetensors
vjepa2
feature-extraction
video
Model card Files Files and versions
xet
Community
4

Instructions to use facebook/vjepa2-vith-fpc64-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use facebook/vjepa2-vith-fpc64-256 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("video-classification", model="facebook/vjepa2-vith-fpc64-256")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("facebook/vjepa2-vith-fpc64-256")
    model = AutoModel.from_pretrained("facebook/vjepa2-vith-fpc64-256")
  • Notebooks
  • Google Colab
  • Kaggle
vjepa2-vith-fpc64-256
13 GB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 4 commits
koustuvs's picture
koustuvs
Update README.md
b5eac87 verified 10 months ago
  • original
    Initial commit 12 months ago
  • .gitattributes
    1.52 kB
    Initial commit 12 months ago
  • README.md
    3.2 kB
    Update README.md 10 months ago
  • config.json
    785 Bytes
    Initial commit 12 months ago
  • model.safetensors
    2.62 GB
    xet
    Initial commit 12 months ago
  • notebook.ipynb
    4.3 kB
    Initial commit 12 months ago
  • notebook_finetuning.ipynb
    545 kB
    Add fine-tuning notebook (#3) 11 months ago
  • video_preprocessor_config.json
    1.3 kB
    Initial commit 12 months ago