Instructions to use facebook/PE-Core-G14-448 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PerceptionEncoder
How to use facebook/PE-Core-G14-448 with PerceptionEncoder:
# Use PE-Core models as CLIP models import core.vision_encoder.pe as pe model = pe.CLIP.from_config("facebook/PE-Core-G14-448", pretrained=True)# Use any PE model as a vision encoder import core.vision_encoder.pe as pe model = pe.VisionTransformer.from_config("facebook/PE-Core-G14-448", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60f5ae715331a595c9959a42ddcde31d99f210dc6d9e1a6961486418d0a4c256
- Size of remote file:
- 9.68 GB
- SHA256:
- 516a20fb30394cc8080344c32d7e49e0e575cf2c6d141977207bf94b3bec192f
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