task_categories:text-classification task_categories:translation task_categories:feature-extraction language:az language:be language:en language:et language:fi language:ka language:ja language:ko language:kk language:lv language:lt language:mn language:no language:pl language:ru language:uk language:zh license:mit size_categories:1K<n<10K format:parquet modality:image library:datasets library:dask library:mlcroissant library:polars region:us code
---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': az
          '1': by
          '2': cn
          '3': en
          '4': es
          '5': fn
          '6': gr
          '7': jp
          '8': ko
          '9': kz
          '10': la
          '11': li
          '12': mo
          '13': 'no'
          '14': pl
          '15': ru
          '16': ua
  splits:
  - name: train
    num_bytes: 1893804579.79
    num_examples: 1987
  - name: test
    num_bytes: 374568135
    num_examples: 339
  download_size: 2423302965
  dataset_size: 2268372714.79
task_categories:
- text-classification
- translation
- feature-extraction
tags:
- code
size_categories:
- 1K<n<10K
license: mit
language:
- az
- be
- en
- et
- fi
- ka
- ja
- ko
- kk
- lv
- lt
- mn
- 'no'
- pl
- ru
- uk
- zh
---
# Dataset Card for "docs_on_several_languages"
This dataset is a collection of different images in different languages.
The set includes the following languages: Azerbaijani, Belorussian, Chinese, English, Estonian, Finnish, Georgian, Japanese, Korean, Kazakh, Latvian, Lithuanian, Mongolian, Norwegian, Polish, Russian, Ukranian.
Each language has a corresponding class label defined. At least 100 images in the entire dataset are allocated per class. This dataset was originally used for the task of classifying the language of a document based on its image, but I hope it can help you in other machine learning tasks.

[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)