Image Feature Extraction
Transformers
Safetensors
ijepa
Inference Endpoints
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  - timm/imagenet-22k-wds
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- # I-JEPA Model (Huge, fine-tuned on IN22K)
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  **I-JEPA** is a method for self-supervised learning. At a high level, I-JEPA predicts the representations of part of an image from the representations of other parts of the same image:
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  1. without relying on pre-specified invariances to hand-crafted data transformations, which tend to be biased for particular downstream tasks,
 
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  - timm/imagenet-22k-wds
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+ # I-JEPA Model (Giant, fine-tuned on IN22K)
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  **I-JEPA** is a method for self-supervised learning. At a high level, I-JEPA predicts the representations of part of an image from the representations of other parts of the same image:
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  1. without relying on pre-specified invariances to hand-crafted data transformations, which tend to be biased for particular downstream tasks,