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mlboydaisuke
/
PE-Core-base-patch16-224-LiteRT

Image Feature Extraction
LiteRT
LiteRT
PerceptionEncoder
on-device
android
gpu
clip
image-encoder
vit
rope
Model card Files Files and versions
xet
Community

Instructions to use mlboydaisuke/PE-Core-base-patch16-224-LiteRT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • LiteRT

    How to use mlboydaisuke/PE-Core-base-patch16-224-LiteRT with LiteRT:

    # No code snippets available yet for this library.
    
    # To use this model, check the repository files and the library's documentation.
    
    # Want to help? PRs adding snippets are welcome at:
    # https://github.com/huggingface/huggingface.js
  • PerceptionEncoder

    How to use mlboydaisuke/PE-Core-base-patch16-224-LiteRT with PerceptionEncoder:

    # Use PE-Core models as CLIP models
    import core.vision_encoder.pe as pe
    
    model = pe.CLIP.from_config("mlboydaisuke/PE-Core-base-patch16-224-LiteRT", pretrained=True)
    # Use any PE model as a vision encoder
    import core.vision_encoder.pe as pe
    
    model = pe.VisionTransformer.from_config("mlboydaisuke/PE-Core-base-patch16-224-LiteRT", pretrained=True)
  • Notebooks
  • Google Colab
  • Kaggle
PE-Core-base-patch16-224-LiteRT
1.52 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
mlboydaisuke's picture
mlboydaisuke
initial commit
c3c5e19 verified 16 days ago
  • .gitattributes
    1.52 kB
    initial commit 16 days ago