Datasets:
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README.md
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---
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dataset_info:
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- config_name: en-af
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features:
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- split: validation
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path: en-zu/validation-*
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---
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---
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annotations_creators:
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- no-annotation
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language_creators:
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- found
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language:
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- af
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- am
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- an
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- ar
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- as
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- az
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- be
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- bg
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- bn
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- br
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- bs
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- ca
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- cs
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- cy
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- da
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- de
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- dz
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- el
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- en
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- eo
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- es
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- et
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- eu
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- fa
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- fi
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- fr
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- fy
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- ga
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- gd
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- gl
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- gu
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- ha
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- he
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- hi
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- hr
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- hu
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- hy
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- id
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- ig
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- is
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- it
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- ja
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- ka
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- kk
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- km
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- kn
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- ko
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- ku
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- ky
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- li
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- lt
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- lv
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- mg
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- mk
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- ml
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- mn
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- mr
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- ms
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- mt
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- my
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- nb
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- ne
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- nl
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- nn
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- 'no'
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- oc
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- or
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- pa
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- pl
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- ps
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- pt
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- ro
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- ru
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- rw
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- se
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- sh
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- si
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- sk
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- sl
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- sq
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- sr
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- sv
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- ta
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- te
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- tg
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- th
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- tk
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- tr
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- tt
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- ug
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- uk
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- ur
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- uz
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- vi
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- wa
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- xh
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- yi
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- yo
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- zh
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- zu
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size_categories:
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- 10M<n<100M
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task_categories:
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- feature-extraction
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- sentence-similarity
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pretty_name: OPUS-100
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tags:
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- sentence-transformers
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dataset_info:
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- config_name: en-af
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features:
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- split: validation
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path: en-zu/validation-*
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---
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# Dataset Card for Parallel Sentences - OPUS-100
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This dataset contains parallel sentences (i.e. English sentence + the same sentences in another language) for numerous other languages. The sentences originate from the [OPUS-100 website](https://opus.nlpl.eu/opus-100.php).
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In particular, this dataset is a reformatting of the [OPUS-100](https://huggingface.co/datasets/Helsinki-NLP/opus-100) dataset.
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## Related Datasets
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The following datasets are also a part of the Parallel Sentences collection:
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* [parallel-sentences-europarl](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-europarl)
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* [parallel-sentences-global-voices](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-global-voices)
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* [parallel-sentences-muse](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-muse)
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* [parallel-sentences-jw300](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-jw300)
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* [parallel-sentences-news-commentary](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-news-commentary)
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* [parallel-sentences-opensubtitles](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-opensubtitles)
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* [parallel-sentences-talks](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-talks)
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* [parallel-sentences-tatoeba](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-tatoeba)
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* [parallel-sentences-wikimatrix](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-wikimatrix)
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* [parallel-sentences-wikititles](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-wikititles)
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Recent additions (May 2024):
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* [parallel-sentences-opus-100](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-opus-100)
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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).
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## Dataset Stats
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* Columns: "english", "non_english"
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* Column types: `str`, `str`
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* Examples:
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```python
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{
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"english": "Run Program",
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"non_english": "Rith Ríomhchlár"
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}
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```
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* Collection strategy: Processing the raw data from [OPUS-100](https://huggingface.co/datasets/Helsinki-NLP/opus-100) and restructuring it into 2 columns: "english" and "non_english".
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* Deduplified: No
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