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---
annotations_creators:
- expert-generated
- found
language_creators:
- found
- expert-generated
license: []
multilinguality:
- translation
pretty_name: opus
size_categories: []
source_datasets: []
tags:
- parallel-corpus
task_categories:
- translation
task_ids: []
---
# Dataset Card for [opus]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
**Disclaimer.** Loading of dataset is slow, thus it may not be feasible when loading at scale. I'd suggest to use the other OPUS datasets on Huggingface which loads a specific corpus.
Loads [OPUS](https://opus.nlpl.eu/) as HuggingFace dataset. OPUS is an open parallel corpus covering 700+ languages and 1100+ datasets.
Given a `src` and `tgt` language, this repository can load *all* available parallel corpus. To my knowledge, other OPUS datasets on Huggingface loads a specific corpus
**Requirements**.
```
pip install pandas
# pip install my fork of `opustools`
git clone https://github.com/larrylawl/OpusTools.git
pip install -e OpusTools/opustools_pkg
```
**Example Usage**.
```
# args follows `opustools`: https://pypi.org/project/opustools/
src="en"
tgt="id"
download_dir="data" # dir to save downloaded files
corpus="bible-uedin" # corpus name. Leave as `None` to download all available corpus for the src-tgt pair.
dataset = load_dataset("larrylawl/opus",
src=src,
tgt=tgt,
download_dir=download_dir,
corpus=corpus)
)
```
**Disclaimer**.
This repository is still in active development. Do make a PR if there're any issues!
### Dataset Summary
[More Information Needed]
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
Available languages can be viewed on the [OPUS API](https://opus.nlpl.eu/opusapi/?languages=True)
## Dataset Structure
### Data Instances
```
{'src': 'In the beginning God created the heavens and the earth .',
'tgt': 'Pada mulanya , waktu Allah mulai menciptakan alam semesta'}
```
### Data Fields
```
features = {
"src": datasets.Value("string"),
"tgt": datasets.Value("string"),
}
```
### Data Splits
Merged all data into train split.
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
Thanks to [@larrylawl](https://larrylawl.github.io/) for adding this dataset. |