This is related to one of my papers. If you are interested, we can discuss the details via email. 😄
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Yu2020
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SigLIP 2: A better multilingual vision language encoder
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SigLIP 2: A better multilingual vision language encoder
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SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic
Understanding, Localization, and Dense Features
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SigLIP 2: A better multilingual vision language encoder
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SigLIP 2: A better multilingual vision language encoder
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"When using the standalone GemmaTokenizerFast make sure to pass padding="max_length" and max_length=64 as that’s how the model was trained." Does Siglip2 support longer text input? If the max_length is set to 256 or 512, will text exceeding 64 be truncated?
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