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Datasets:
PuzzleBench
/
Recaptioned_LAION

Tasks:
Image-to-Text
Text-to-Image
Languages:
English
Size:
100K<n<1M
Tags:
laion
recaptioned
vision-language-alignment
clip-training
webdataset
Libraries:
WebDataset
License:
Dataset card Data Studio Files
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  1. .gitattributes +1 -0
  2. README.md +110 -0
  3. metadata.csv +3 -0
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.gitattributes CHANGED
@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
 
 
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
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+ metadata.csv filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,110 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: cc-by-4.0
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+ task_categories:
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+ - image-to-text
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+ - text-to-image
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+ language:
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+ - en
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+ tags:
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+ - laion
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+ - recaptioned
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+ - vision-language-alignment
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+ - clip-training
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+ - webdataset
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+ pretty_name: Recaptioned LAION (Gemma-3-27B)
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+ size_categories:
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+ - 100K<n<1M
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+ ---
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+
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+ # Recaptioned LAION
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+
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+ A subset of LAION recaptioned with **Gemma-3-27B-IT**. Each image is paired
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+ with a single descriptive sentence (~20–30 words) generated by Gemma using
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+ the prompt:
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+
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+ > *Describe this image in 20-30 words. Do not include any preamble or
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+ > introduction, just the description.*
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+
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+ This dataset is used by the **PuzzleBench** project for vision/text
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+ alignment training.
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+
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+ ## Stats
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+
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+ | | |
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+ |---|---:|
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+ | Samples | 508,025 |
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+ | Image resolution | up to 1500×1500 (varies) |
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+ | Format | JPEG |
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+ | Caption type | Gemma-3-27B recaption (declarative, ~130 chars avg) |
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+ | Shards | 30 webdataset `.tar` files (~2.4 GB each) |
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+ | Total size | ~72 GB |
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+
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+ ## Format: WebDataset
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+
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+ The dataset ships as **30 webdataset-compatible tar shards**, the de facto
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+ standard for large image-text corpora (used by LAION-400M, LAION-5B, CLIP
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+ training pipelines, etc.). Each shard is a flat tar containing:
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+
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+ ```
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+ shards-00000.tar
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+ ├── 000000.jpg # raw image bytes
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+ ├── 000000.txt # caption (utf-8)
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+ ├── 000001.jpg
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+ ├── 000001.txt
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+ └── ...
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+ ```
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+
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+ A `metadata.csv` with the same `image_id, url, caption` is also shipped
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+ alongside for non-webdataset consumers.
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+
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+ ## Usage
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+
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+ ### With `webdataset` (streaming, no extraction needed)
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+
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+ ```python
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+ import webdataset as wds
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+
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+ url = "https://huggingface.co/datasets/PuzzleBench/Recaptioned_LAION/resolve/main/shards-{00000..00029}.tar"
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+ ds = (
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+ wds.WebDataset(url)
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+ .decode("pil")
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+ .to_tuple("jpg", "txt")
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+ )
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+
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+ for image, caption in ds:
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+ # image: PIL.Image
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+ # caption: str
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+ ...
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+ ```
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+
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+ ### With `huggingface_hub` snapshot + local extraction
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+
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+ ```python
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+ from huggingface_hub import snapshot_download
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+
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+ snapshot_download(
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+ repo_id="PuzzleBench/Recaptioned_LAION",
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+ repo_type="dataset",
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+ local_dir="recaptioned_laion",
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+ )
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+ ```
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+
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+ ### With `pandas` (captions only, no images)
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+
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+ ```python
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+ import pandas as pd
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+ df = pd.read_csv("hf://datasets/PuzzleBench/Recaptioned_LAION/metadata.csv")
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+ # columns: image_id, url, caption
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+ ```
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+
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+ ## License
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+
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+ This dataset of recaptions is released under **CC BY 4.0**. The underlying
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+ images are sourced from public LAION URLs and retain their original
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+ licensing — please consult the LAION usage terms when redistributing or
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+ training on the image content.
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+
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+ ## Citation
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+
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+ If you use this dataset, please cite the PuzzleBench project and credit
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+ the LAION corpus and the Gemma-3 recaptioning model.
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