Slimmable ConvNeXt adapts ConvNeXt for width-adaptive inference using LayerNorm and inverted bottlenecks, reaching 80.8% top-1 at 4.5 GMACs and outperforming HydraViT, MatFormer, and SortedNet on ImageNet-1k.
Mat- Former: Nested transformer for elastic inference.Advances in Neural Information Processing Systems, 37:140535– 140564, 2024
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Slimmable ConvNeXt: Width-Adaptive Inference for Efficient Multi-Device Deployment
Slimmable ConvNeXt adapts ConvNeXt for width-adaptive inference using LayerNorm and inverted bottlenecks, reaching 80.8% top-1 at 4.5 GMACs and outperforming HydraViT, MatFormer, and SortedNet on ImageNet-1k.