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* ` vit_so150m2_patch16_reg1_gap_256.sbb_e200_in12k_ft_in1k ` - 87.3% top-1
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* ` vit_so150m2_patch16_reg4_gap_256.sbb_e200_in12k `
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* Updated InternViT-300M '2.5' weights
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+ * Release 1.0.15
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## Feb 1, 2025
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* FYI PyTorch 2.6 & Python 3.13 are tested and working w/ current main and released version of ` timm `
@@ -452,6 +453,8 @@ All model architecture families include variants with pretrained weights. There
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* SelecSLS - https://arxiv.org/abs/1907.00837
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* Selective Kernel Networks - https://arxiv.org/abs/1903.06586
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* Sequencer2D - https://arxiv.org/abs/2205.01972
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+ * SigLIP (image encoder) - https://arxiv.org/abs/2303.15343
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+ * SigLIP 2 (image encoder) - https://arxiv.org/abs/2502.14786
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* Swin S3 (AutoFormerV2) - https://arxiv.org/abs/2111.14725
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* Swin Transformer - https://arxiv.org/abs/2103.14030
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* Swin Transformer V2 - https://arxiv.org/abs/2111.09883
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