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README.md

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@@ -24,8 +24,9 @@ We provide more details about our full collection of pretrained models [here](do
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| ViT-L/14 | DataComp-1B | 224px | 13B | 79.2% |
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| ViT-G/14 | LAION-2B | 224px | 34B | 80.1% |
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| ViT-L/14 [(Original CLIP)](https://arxiv.org/abs/2103.00020) | WIT | 224px | 13B | 75.5% |
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| ViT-L/14-quickgelu [(Original CLIP)](https://arxiv.org/abs/2103.00020) | WIT | 224px | 13B | 75.5% |
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| ViT-SO400M/14 [(SigLIP)](https://arxiv.org/abs/2303.15343) | WebLI | 224px | 45B | 82.0% |
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| ViT-L/14 [(DFN)](https://arxiv.org/abs/2309.17425) | DFN-2B | 224px | 39B | 82.2% |
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| ViT-SO400M-14-SigLIP-384 [(SigLIP)](https://arxiv.org/abs/2303.15343) | WebLI | 384px | 45B | 83.1% |
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| ViT-H/14-quickgelu [(DFN)](https://arxiv.org/abs/2309.17425) | DFN-5B | 224px | 39B | 83.4% |
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| ViT-H-14-378-quickgelu [(DFN)](https://arxiv.org/abs/2309.17425) | DFN-5B | 378px | 44B | 84.4% |

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