| # Parallel Sentences for 50+ languages |
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| > [!NOTE] |
| > This repository contains raw datasets, all of which have also been formatted for easy training in the [Parallel Sentences Datasets](https://huggingface.co/collections/sentence-transformers/parallel-sentences-datasets-6644d644123d31ba5b1c8785) collection. We recommend looking there first. |
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| This repository contains parallel sentences (i.e. English + same sentences in other language) for 50+ different languages in a simple tsv.gz format: |
| ``` |
| english_sentences\tsentence_in_other_language |
| ``` |
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| Sentences stem from the [OPUS website](https://opus.nlpl.eu/). |
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| The following datasets are included: |
| - [Europarl](https://opus.nlpl.eu/Europarl.php) |
| - [GlobalVoices](https://opus.nlpl.eu/GlobalVoices.php) |
| - [JW300](https://opus.nlpl.eu/JW300.php) |
| - [MUSE](https://github.com/facebookresearch/MUSE) |
| - [News-Commentary](https://opus.nlpl.eu/News-Commentary.php) |
| - [OpenSubtitles](https://opus.nlpl.eu/OpenSubtitles.php) |
| - [Tatoeba](https://tatoeba.org/) |
| - Talks - Custom translated transcripts of talks |
| - [WikiMatrix](https://opus.nlpl.eu/WikiMatrix.php) |
| - WikiTitles - Custom dataset with parallel Wikipedia titles |
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| ## Usage |
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| These sentences can be used to train multi-lingual sentence embedding models. For more details, see [SBERT.net - Multilingual-Model](https://www.sbert.net/examples/training/multilingual/README.html) |
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| **This dataset can not yet be used with Hugging Face dataset library. You must download the individual TSV files.** |
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