Instructions to use facebook/PE-Core-L14-336 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PerceptionEncoder
How to use facebook/PE-Core-L14-336 with PerceptionEncoder:
# Use PE-Core models as CLIP models import core.vision_encoder.pe as pe model = pe.CLIP.from_config("facebook/PE-Core-L14-336", 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-L14-336", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f09e8c98f1609470556a78bc2741423305110aec67ee6616f7a98a4ec521735
- Size of remote file:
- 2.68 GB
- SHA256:
- 0cdab5b338cbaa1e7a5dcd1b2fb4c9f4d5df1abd289564658edbab64a650e7e8
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