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[https://huggingface.co/papers/2507.22062 Source : huggingface] | [https://huggingface.co/papers/2507.22062 Source : huggingface] | ||
[https://vladbogo.substack.com/p/metaclip-2-a-worldwide-scaling-recipe Source : substack] | |||
[[Catégorie:vocabulary]] | [[Catégorie:vocabulary]] |
Dernière version du 12 août 2025 à 09:55
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Définition
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MetaCLIP
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MetaCLIP
The first recipe for training CLIP models from scratch on worldwide web-scale image-text pairs spanning 300+ languages. The work addresses the challenge of scaling CLIP beyond English-only data while avoiding the "curse of multilinguality" - where multilingual models perform worse on English tasks than their English-only counterparts. The paper demonstrates that with proper data curation, metadata construction, and training framework design, English and non-English data can actually benefit each other mutually. MetaCLIP 2, trained on worldwide web-scale image-text pairs, improves zero-shot classification and multilingual benchmarks without system-level confounding factors.
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