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This repository contains data associated with the paper "Scaling Text-to-Image Diffusion Transformers with Representation Autoencoders".
The dataset is used for training and evaluating Scale-RAE, a framework that investigates scaling Representation Autoencoders (RAEs) for large-scale, freeform text-to-image (T2I) generation. It includes data used for scaling RAE decoders beyond ImageNet, featuring web, synthetic, and text-rendering data… See the full description on the dataset page:
https://huggingface.co/datasets/nyu-visionx/scale-rae-data.