Instructions to use bep256/PE-Core-L14-336-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PerceptionEncoder
How to use bep256/PE-Core-L14-336-ONNX with PerceptionEncoder:
# Use PE-Core models as CLIP models import core.vision_encoder.pe as pe model = pe.CLIP.from_config("bep256/PE-Core-L14-336-ONNX", pretrained=True)# Use any PE model as a vision encoder import core.vision_encoder.pe as pe model = pe.VisionTransformer.from_config("bep256/PE-Core-L14-336-ONNX", pretrained=True) - Notebooks
- Google Colab
- Kaggle
PE Core L/14 336
This is an ONNX conversion of Meta's PE Core L/14 336, exported from the timm/OpenCLIP checkpoint.
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Base model
facebook/PE-Core-L14-336