NLLB-CLIP -- train performant multilingual image retrieval model on a budget
Paper • 2309.01859 • Published • 3
Model Summary
NLLB-CLIP is a model that combines a text encoder from the NLLB model and an image encoder from the LAION CLIP. This allows us to extend the model capabilities to 201 languages of the Flores-200. NLLB-CLIP sets state-of-the-art on the Crossmodal-3600 dataset by performing very well on low-resource languages. You can find more details about the model in the paper.
Acknowledgements
I thank ML Collective for providing Google Cloud compute resources to train the OpenCLIP-compatible version of NLLB-CLIP.
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