Cao

This is a standardized, high-efficiency version of the JUNJIE99/MegaPairs dataset. Why use this version? The original dataset is distributed as a massive Tar archive containing millions of images, accompanied by a separate JSONL annotation file. Each row in the dataset represents a Universal Retrieval Pair (Query -> Target). You can load this dataset directly using the datasets library. This is the easiest way. The library handles the Arrow files automatically. from datasets import loaddataset dataset = loaddataset("86Cao/MegaPairs-Standard", split="train") print(f"Total samples: {len(dataset)}") sample = dataset[0] print(f"Text: {sample['querytexts'][0]}") sample['queryimage'].show() #…