README.md

metadata

license: cc-by-4.0
task_categories:
  - image-to-text
  - text-to-image
language:
  - en
tags:
  - laion
  - recaptioned
  - vision-language-alignment
  - clip-training
  - webdataset
pretty_name: Recaptioned LAION (Gemma-3-27B)
size_categories:
  - 100K<n<1M

Recaptioned LAION

A subset of LAION recaptioned with Gemma-3-27B-IT. Each image is paired with a single descriptive sentence (~20–30 words) generated by Gemma using the prompt:

Describe this image in 20-30 words. Do not include any preamble or introduction, just the description.

This dataset is used by the PuzzleBench project for vision/text alignment training.

Stats

Samples	508,025
Image resolution	up to 1500×1500 (varies)
Format	JPEG
Caption type	Gemma-3-27B recaption (declarative, ~130 chars avg)
Shards	30 webdataset .tar files (~2.4 GB each)
Total size	~72 GB

Format: WebDataset

The dataset ships as 30 webdataset-compatible tar shards, the de facto standard for large image-text corpora (used by LAION-400M, LAION-5B, CLIP training pipelines, etc.). Each shard is a flat tar containing:

shards-00000.tar
├── 000000.jpg     # raw image bytes
├── 000000.txt     # caption (utf-8)
├── 000001.jpg
├── 000001.txt
└── ...

A metadata.csv with the same image_id, url, caption is also shipped alongside for non-webdataset consumers.

Usage

With webdataset (streaming, no extraction needed)

import webdataset as wds

url = "https://huggingface.co/datasets/PuzzleBench/Recaptioned_LAION/resolve/main/shards-{00000..00029}.tar"
ds = (
    wds.WebDataset(url)
    .decode("pil")
    .to_tuple("jpg", "txt")
)

for image, caption in ds:
    # image: PIL.Image
    # caption: str
    ...

With huggingface_hub snapshot + local extraction

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="PuzzleBench/Recaptioned_LAION",
    repo_type="dataset",
    local_dir="recaptioned_laion",
)

With pandas (captions only, no images)

import pandas as pd
df = pd.read_csv("hf://datasets/PuzzleBench/Recaptioned_LAION/metadata.csv")
# columns: image_id, url, caption

License

This dataset of recaptions is released under CC BY 4.0. The underlying images are sourced from public LAION URLs and retain their original licensing — please consult the LAION usage terms when redistributing or training on the image content.

Citation

If you use this dataset, please cite the PuzzleBench project and credit the LAION corpus and the Gemma-3 recaptioning model.