README.md

metadata

configs:
  - config_name: default
    data_files:
      - split: train
        path: train-*
      - split: validation
        path: validation-*
dataset_info:
  features:
    - name: texts
      sequence: string
    - name: images
      sequence: image
    - name: metadata
      list:
        - name: document_url
          dtype: string
        - name: unformatted_src
          dtype: string
        - name: src
          dtype: string
        - name: formatted_filename
          dtype: string
        - name: alt_text
          dtype: string
        - name: rendered_width
          dtype: int64
        - name: rendered_height
          dtype: int64
        - name: original_width
          dtype: int64
        - name: original_height
          dtype: int64
        - name: format
          dtype: string
    - name: general_metadata
      struct:
        - name: url
          dtype: string
        - name: warc_filename
          dtype: string
        - name: warc_record_offset
          dtype: int64
        - name: warc_record_length
          dtype: int64
task_categories:
  - image-text-to-text
language:
  - en
size_categories:
  - 1K<n<10K
tags:
  - multimodal
  - interleaved
  - pretraining

Tiny-OBELICS (Debug Dataset)

Tiny-OBELICS is a curated, 100% offline-compatible multimodal debug dataset of interleaved document-image examples drawn from the first shard of HuggingFaceM4/OBELICS.

All image bytes are stored directly inside the Parquet shards using Hugging Face's native Image feature type. No CDN dependencies, no dead links, no download bubbles at training time.

Dataset Structure

Parallel-lists layout matching the original OBELICS schema.

Column	Type	Description
texts	list[str|null]	Text segments interleaved with images
images	list[image|null]	PIL images (or None for text-only slots)
metadata	list[struct|null]	Per-image metadata (dimensions, src, alt-text, …)
general_metadata	struct	Document-level crawl info (url, warc offset/length)

Shard Policy

• Shards are bounded by raw image byte size (~25MB per shard), not by row count.
• Any document where one or more images failed to download is discarded entirely.
• Images are converted to RGB and have metadata stripped to ensure clean serialization.
• Original image width and height are always calculated directly from the verified PIL image object.

Usage

from datasets import load_dataset

# Load train split
ds_train = load_dataset("akzsh/tiny-obelics", split="train")
print(ds_train)

# Load validation split
ds_val = load_dataset("akzsh/tiny-obelics", split="validation")
print(ds_val)

row = ds_train[0]
for text, img in zip(row["texts"], row["images"]):
    if text: print("[Text]", text[:80])
    elif img: print("[Image]", img.size)

Source

Processed subset of HuggingFaceM4/OBELICS.