{"url":"/dataset/jft-3b","name":"JFT-3B","full_name":"JFT-3B","description_markdown":"**JFT-3B** is an internal Google dataset and a larger version of the JFT-300M dataset. It consists of nearly 3 billion images, annotated with a class-hierarchy of around 30k labels via a semi-automatic pipeline. In other words, the data and associated labels are noisy.","description_withheld":null,"homepage":"","introduced_date":"2021-06-08","introduced_date_note":null,"introduced_by":{"paper":"/paper/scaling-vision-transformers","title":"Scaling Vision Transformers","first_author":"Xiaohua Zhai","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"}],"languages":[],"variants":["JFT-3B"],"data_loaders":[],"num_papers_in_archive":41,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}