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---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': az
'1': be
'2': en
'3': et
'4': fn
'5': gr
'6': ja
'7': kk
'8': ko
'9': lt
'10': lv
'11': mn
'12': 'no'
'13': pl
'14': ru
'15': uk
'16': zh
splits:
- name: train
num_bytes: 7057770706.296
num_examples: 2006
- name: test
num_bytes: 1246282602.0
num_examples: 339
download_size: 7700053691
dataset_size: 8304053308.296
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
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
# Dataset Card for "docs_on_several_languages"
This dataset is a collection of different images in different languages.
The daset includes the following languages: Azerbaijani (az: 0), Belorussian (be: 1), Chinese (zh: 16), English (en: 2), Estonian (et: 3), Finnish (fn: 4), Georgian (gr: 5), Japanese (ja: 6), Korean (ko: 7), Kazakh (kk: 8), Latvian (lv: 10), Lithuanian (lt: 9), Mongolian (mn: 11), Norwegian (no: 12), Polish (pl: 13), Russian (ru: 14), Ukranian (uk: 15).
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. |