Datasets:
File size: 16,794 Bytes
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---
language:
- en
- multilingual
- ar
- bg
- cs
- da
- de
- el
- es
- et
- fa
- fi
- fr
- gu
- he
- hi
- hr
- hu
- hy
- id
- it
- ja
- ka
- ko
- lt
- lv
- mk
- mn
- mr
- my
- nl
- pl
- pt
- ro
- ru
- sk
- sl
- sq
- sv
- th
- tr
- uk
- ur
- vi
size_categories:
- 10M<n<100M
task_categories:
- feature-extraction
- sentence-similarity
pretty_name: JW300
tags:
- sentence-transformers
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---
# Dataset Card for Parallel Sentences - JW300
This dataset contains parallel sentences (i.e. English sentence + the same sentences in another language) for numerous other languages. Most of the sentences originate from the [OPUS website](https://opus.nlpl.eu/).
In particular, this dataset contains the [JW300](https://opus.nlpl.eu/JW300.php) dataset.
## Related Datasets
The following datasets are also a part of the Parallel Sentences collection:
* [parallel-sentences-europarl](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-europarl)
* [parallel-sentences-global-voices](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-global-voices)
* [parallel-sentences-muse](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-muse)
* [parallel-sentences-jw300](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-jw300)
* [parallel-sentences-news-commentary](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-news-commentary)
* [parallel-sentences-opensubtitles](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-opensubtitles)
* [parallel-sentences-talks](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-talks)
* [parallel-sentences-tatoeba](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-tatoeba)
* [parallel-sentences-wikimatrix](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-wikimatrix)
* [parallel-sentences-wikititles](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-wikititles)
* [parallel-sentences-ccmatrix](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-ccmatrix)
These datasets can be used to train multilingual sentence embedding models. For more information, see [sbert.net - Multilingual Models](https://www.sbert.net/examples/training/multilingual/README.html).
## Dataset Subsets
### `all` subset
* Columns: "english", "non_english"
* Column types: `str`, `str`
* Examples:
```python
{
"english": "It will really help me. I am a compulsive TV watcher.",
"non_english": "سيكون هذا الفصل خير مساعد لي ."
}
```
* Collection strategy: Combining all other subsets from this dataset.
* Deduplified: No
### `en-...` subsets
* Columns: "english", "non_english"
* Column types: `str`, `str`
* Examples:
```python
{
"english": "But then you realize you do not have any money with you to pay for the refreshment.",
"non_english": "Namun, kemudian Anda sadar bahwa Anda tidak punya uang untuk membelinya."
}
```
* Collection strategy: Processing the raw data from [parallel-sentences](https://huggingface.co/datasets/sentence-transformers/parallel-sentences) and formatting it in Parquet, followed by deduplication.
* Deduplified: Yes |