|
--- |
|
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](https://huggingface.co/datasets/yhavinga/ccmatrix)**, with Japanese and English pairs. |
|
|
|
### How to use |
|
|
|
It is used in much the same way as **[yhavinga/ccmatrix](https://huggingface.co/datasets/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: |
|
|
|
```json |
|
{ |
|
'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](https://huggingface.co/datasets/yhavinga/ccmatrix)** readme. |
|
The following is taken from **[yhavinga/ccmatrix](https://huggingface.co/datasets/yhavinga/ccmatrix)**: |
|
|
|
IMPORTANT: Please cite reference [2][3] if you use this data. |
|
|
|
1. **[CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data](https://arxiv.org/abs/1911.00359)** |
|
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](https://arxiv.org/abs/1911.04944)** by *Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin*. |
|
3. **[Beyond English-Centric Multilingual Machine Translation](https://arxiv.org/abs/2010.11125)** 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](https://www.aclweb.org/anthology/L12-1246/)** by *Jörg Tiedemann*. |
|
|