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CLIP-convnext_large_d_320.laion2B-s29B-b131K-ft-soup

Zero-Shot Image Classification
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@@ -34,8 +34,8 @@ At 320x320, the ConvNext-Large-D is significantly more efficient than the L/14 m
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  | Model | Dataset | Resolution | AugReg | Top-1 ImageNet Zero-Shot (%) |
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  | ----- | ------- | ---------- | ------------ | --------- |
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  | [convnext_large_d.laion2b_s26b_b102k-augreg](https://huggingface.co/laion/CLIP-convnext_large_d.laion2B-s26B-b102K-augreg) | LAION-2B | 256x256 | RRC (0.33, 1.0), RE (0.35), SD (0.1), D(0.1) | 75.9 |
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- | [convnext_large_d_320.laion2b_s29b_b131k-augreg-ft](https://huggingface.co/laion/CLIP-convnext_large_d_320.laion2B-s29B-b131K-augreg-ft) | LAION-2B | 320x320 | RRC (0.5, 1.0), RE (0.4), SD (0.1), D(0.0) | 76.6 |
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- | [convnext_large_d_320.laion2b_s29b_b131k-augreg-ft-soup](https://huggingface.co/laion/CLIP-convnext_large_d_320.laion2B-s29B-b131K-augreg-ft-soup) | LAION-2B | 320x320 | RRC (0.5, 1.0), RE (0.4), SD (0.1), D(0.0) | 76.9 |
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  RRC = Random Resize Crop (crop pcts), RE = Random Erasing (prob), SD = Stochastic Depth (prob) -- image tower only, D = Dropout (prob) -- image tower head only
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  | Model | Dataset | Resolution | AugReg | Top-1 ImageNet Zero-Shot (%) |
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  | ----- | ------- | ---------- | ------------ | --------- |
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  | [convnext_large_d.laion2b_s26b_b102k-augreg](https://huggingface.co/laion/CLIP-convnext_large_d.laion2B-s26B-b102K-augreg) | LAION-2B | 256x256 | RRC (0.33, 1.0), RE (0.35), SD (0.1), D(0.1) | 75.9 |
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+ | [convnext_large_d_320.laion2b_s29b_b131k-ft](https://huggingface.co/laion/CLIP-convnext_large_d_320.laion2B-s29B-b131K-ft) | LAION-2B | 320x320 | RRC (0.5, 1.0), RE (0.4), SD (0.1), D(0.0) | 76.6 |
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+ | [convnext_large_d_320.laion2b_s29b_b131k-ft-soup](https://huggingface.co/laion/CLIP-convnext_large_d_320.laion2B-s29B-b131K-ft-soup) | LAION-2B | 320x320 | RRC (0.5, 1.0), RE (0.4), SD (0.1), D(0.0) | 76.9 |
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  RRC = Random Resize Crop (crop pcts), RE = Random Erasing (prob), SD = Stochastic Depth (prob) -- image tower only, D = Dropout (prob) -- image tower head only
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