Instructions to use LibreYOLO/LibrePEt16-cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PerceptionEncoder
How to use LibreYOLO/LibrePEt16-cls with PerceptionEncoder:
# Use any PE model as a vision encoder import core.vision_encoder.pe as pe model = pe.VisionTransformer.from_config("LibreYOLO/LibrePEt16-cls", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a6626e46057557531ba5a71a18f6fffdcb814d9a6228891b07f2666362b739c
- Size of remote file:
- 278 MB
- SHA256:
- b6a1e3b6eb8d40c5f48de0dc9e58fbdadf4c6c6ea284807f8024a87d59702d1e
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