README.md

metadata

dataset_info:
  features:
    - name: id
      dtype: int32
    - name: score
      dtype: float32
    - name: translation
      dtype:
        translation:
          languages:
            - en
            - ja
  splits:
    - name: train
      num_bytes: 6415875645
      num_examples: 40883733
  download_size: 4563432887
  dataset_size: 6415875645
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: unknown
task_categories:
  - translation
  - text2text-generation
language:
  - en
  - ja

Dataset Card for CCMatrix-en-ja

Dataset Summary

This corpus is extracted from yhavinga/ccmatrix, with Japanese and English pairs.

How to use

It is used in much the same way as yhavinga/ccmatrix. The only difference is that you do not have to specify the language.

from datasets import load_dataset
dataset = load_dataset("yhavinga/ccmatrix")

If data loading times are too long and boring, use Streaming.

from datasets import load_dataset
dataset = load_dataset("yhavinga/ccmatrix", streaming=True)

Dataset Structure

Data Instances

For example:

{
        'id': 0,
        'score': 1.2499920129776,
        'translation': {
            'en': 'Such is God’s forgiveness.',
            'ja': 'それは神の赦しの故だ。'
        }
  }

Data Fields

Each example contains an integer id starting with 0, a score, and a translation dictionary with the language 1 and language 2 texts.

Data Splits

Only a train split is provided.

Citation Information

Follow the instructions described in the yhavinga/ccmatrix readme. The following is taken from yhavinga/ccmatrix:

IMPORTANT: Please cite reference [2][3] if you use this data.

1. CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data by Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzmán, Armand Jouli and Edouard Grave.
2. CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB by Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin.
3. Beyond English-Centric Multilingual Machine Translation by Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines, Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky, Sergey Edunov, Edouard Grave, Michael Auli, and Armand Joulin.

This HuggingFace CCMatrix dataset is a wrapper around the service and files prepared and hosted by OPUS:

• Parallel Data, Tools and Interfaces in OPUS by Jörg Tiedemann.