zlab-princeton/i1-gptedit-tfrecord

i1: A Simple and Fully Open Recipe for Strong Text-to-Image Models Boya Zeng, Tianze Luo, Shu Pu, Jucheng Shen, Taiming Lu, Gabriel Sarch, Zhuang Liu Princeton University [arXiv][code][model][project page] Overview To prepare the dataset for training, we store the image-caption pairs as TFRecords. This HuggingFace dataset contains the TFRecords corresponding to the gptedit dataset at 256×256 resolution. It also serves as an example of what a dataset processed using our… See the full description on the dataset page: https://huggingface.co/datasets/zlab-princeton/i1-gptedit-tfrecord.

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