%0 Conference Paper
%A Schuhmann, Christoph
%A Vencu, Richard
%A Beaumont, Romain
%A Kaczmarczyk, Robert
%A Mullis, Clayton
%A Katta, Aarush
%A Coombes, Theo
%A Jitsev, Jenia
%A Komatsuzaki, Aran
%T LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs
%M FZJ-2022-00923
%P 5 p.
%D 2021
%X Multi-modal language-vision models trained on hundreds of millions of image-textpairs (e.g. CLIP, DALL-E) gained a recent surge, showing remarkable capability toperform zero- or few-shot learning and transfer even in absence of per-sample labelson target image data. Despite this trend, to date there has been no publicly availabledatasets of sufficient scale for training such models from scratch. To address thisissue, in a community effort we build and release for public LAION-400M, adataset with CLIP-filtered 400 million image-text pairs, their CLIP embeddingsand kNN indices that allow efficient similarity search
%B NeurIPS Workshop Datacentric AI
%C 14 Dec 2021 - 14 Dec 2021, online (online)
Y2 14 Dec 2021 - 14 Dec 2021
M2 online, online
%F PUB:(DE-HGF)8
%9 Contribution to a conference proceedings
%U https://juser.fz-juelich.de/record/905696