Datasets:

Languages:
Japanese
ArXiv:
License:
Dataset Viewer
The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    TypeError
Message:      list_() takes at least 1 positional argument (0 given)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 165, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1664, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1621, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 992, in get_module
                  dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 378, in from_dataset_card_data
                  {
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 379, in <dictcomp>
                  dataset_info_yaml_dict.get("config_name", "default"): DatasetInfo._from_yaml_dict(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 317, in _from_yaml_dict
                  yaml_data["features"] = Features._from_yaml_list(yaml_data["features"])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 2035, in _from_yaml_list
                  return cls.from_dict(from_yaml_inner(yaml_data))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 2031, in from_yaml_inner
                  return {name: from_yaml_inner(_feature) for name, _feature in zip(names, obj)}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 2031, in <dictcomp>
                  return {name: from_yaml_inner(_feature) for name, _feature in zip(names, obj)}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 2020, in from_yaml_inner
                  Value(obj["dtype"])
                File "<string>", line 5, in __init__
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 528, in __post_init__
                  self.pa_type = string_to_arrow(self.dtype)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 148, in string_to_arrow
                  return pa.__dict__[datasets_dtype + "_"]()
                File "pyarrow/types.pxi", line 4398, in pyarrow.lib.list_
              TypeError: list_() takes at least 1 positional argument (0 given)

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Dataset Card for MOMIJI

MOMIJI (Modern Open Multimodal Japanese filtered Dataset) is a large-scale, carefully curated public dataset of image-text–interleaved web documents. The dataset was extracted from Common Crawl dumps covering February 2024 – January 2025 and contains roughly 56M Japanese documents, 110B characters, and 249M images. Details of the collection and filtering pipeline will be described in a forthcoming paper.

Image-text–interleaved data is generally used to train large vision-language models (LVLMs) such as LLaVA-OneVision, Idefics 2, NVILA, and Qwen 2.5-VL. Using MOMIJI, we trained our proposed model Heron-NVILA-Lite.

Following OBELICS, we provide an interactive visualization that allows users to explore the contents of MOMIJI. The map shows a subset of 1M of the 56M documents.

MOMIJI Nomic map

Warning and Disclaimer: This content may unintentionally include expressions or information that some may find inappropriate. Please view it at your own discretion and responsibility.

Data Fields

Example (truncated):

{
  "docId": "CC-MAIN-20240518121005-20240518151005-00454_00091",
  "url": "https://tanaka-yuki.com/spring/post-10813/",
  "text_list": [
    "大学の卒業式には、男性ならスーツを選ぶ方がとても多いですが、どんなスーツを着用すればいいのか?と悩みますよね。",
    "...",
    "大学卒業式で男性はスーツが基本",
    "<image1>",
    "...",
    "安定感ならシングルデザイン",
    "<image2>",
    "..."
  ],
  "text": "大学の卒業式には、男性ならスーツを選ぶ方がとても多いですが、どんなスーツを着用すればいいのか?と悩みますよね.\n ...",
  "image_info": [
    {
      "placeholder": "<image1>",
      "url": "https://tanaka-yuki.com/wp-content/uploads/2022/12/collage-1-1.webp",
      "width": 1080,
      "height": 620,
      "original_width": 1080,
      "original_height": 620,
      "exif": "{}",
      "alt": "大学卒業式で男性はスーツが基本"
    },
    "..."
  ]
}

Each sample has five top-level fields:

Field Type Description
docId str Unique ID derived from the source Common Crawl ID
url str Source web URL
text_list list\<str\> Document text split into individual segments
text str Full text with image placeholders
image_info list\<dict\> List of image metadata:
placeholder (str)
url (str)
original_width / original_height (int)
exif (dict, optional)
alt (str, optional)

Size and Splits

MOMIJI contains about 56M Japanese web documents. Because images are provided only as URLs (no binary data), the dataset is roughly 150 GB.

MOMIJI Statistics

Metric Value
Number of documents 56,119,639
Number of images 249,745,953
Total characters 109,980,725,957
Average characters/Doc. 1,959
Average images/Doc. 4.45

Below is a bar chart of document counts by number of images (documents with ≥ 30 images are omitted for readability):

Content Warning

Although an NSFW filter was applied, some links or text samples may still be disturbing. The dataset is intended for scientific or safety analyses by trained researchers.

Disclaimer

MOMIJI does NOT distribute image binaries—only links and metadata. We are not responsible for content accessible via those links. Filtering was performed automatically due to the dataset’s scale.

License Information

CC-BY-4.0

Acknowledgements

This model is based on results obtained from a project, JPNP20017, subsidized by the New Energy and Industrial Technology Development Organization (NEDO).

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