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Aya Header

This is a re-upload of the aya_collection, and only differs in the structure of upload. While the original aya_collection is structured by folders split according to dataset name, this dataset is split by language. We recommend you use this version of the dataset if you are only interested in downloading all of the Aya collection for a single or smaller set of languages.

Dataset Summary

The Aya Collection is a massive multilingual collection consisting of 513 million instances of prompts and completions covering a wide range of tasks. This collection incorporates instruction-style templates from fluent speakers and applies them to a curated list of datasets, as well as translations of instruction-style datasets into 101 languages. Aya Dataset, a human-curated multilingual instruction and response dataset, is also part of this collection. See our paper for more details regarding the collection.

  • Curated by: Contributors of Aya Open Science Intiative

  • Language(s): 115 languages

  • License: Apache 2.0

  • Aya Datasets Family:

    Name Explanation
    aya_dataset Human-annotated multilingual instruction finetuning dataset, comprising over 204K instances across 65 languages.
    aya_collection Created by applying instruction-style templates from fluent speakers to 44 datasets, including translations of 19 instruction-style datasets into 101 languages. This collection structured based on dataset level subsets. An alternative version of the collection structured by language subsets is also available.
    aya_collection_language_split Aya Collection structured based on language level subsets.
    aya_evaluation_suite A diverse evaluation set for multilingual open-ended generation, featuring 250 culturally grounded prompts in 7 languages, 200 translated prompts in 24 languages, and human-edited versions selected for cross-cultural relevance from English Dolly in 6 languages.
    aya_redteaming A red-teaming dataset consisting of harmful prompts in 8 languages across 9 different categories of harm with explicit labels for "global" and "local" harm.

Dataset

The Aya Collection is a comprehensive, large corpus of datasets that can be used by researchers around the world to train multilingual models. Our goal is only to include datasets with permissive licensing for manipulation and redistribution.

The Aya Collection consists of three different sources of data:

  1. Templated data: We collaborated with fluent speakers to create templates that allowed for the automatic expansion of existing datasets into various languages.
  2. Translated data: We translated a hand-selected subset of 19 datasets into 101 languages (114 dialects) using the NLLB 3.3B parameter machine translation model.
  3. Aya Dataset: We release the Aya Dataset as a subset of the overall collection. This is the only dataset in the collection that is human-annotated in its entirety.

Load with Datasets

To load this dataset with Datasets, you'll need to install Datasets as pip install datasets --upgrade and then use the following code:

from datasets import load_dataset

dataset = load_dataset("CohereLabs/aya_collection_language_split", "english")

In the above code snippet, "english" refers to a subset of the aya_collection. You can load other subsets by specifying its name at the time of loading the dataset.

Data Instances

An example of a train instance looks as follows:

{'id': 246001,
 'inputs': 'The following query in English is taken from the geography category. What could be the answer to the question?\nWhat is the seventh tallest mountain in North America?',
 'targets': 'The answer is Mount Lucania.',
 'dataset_name': 'Mintaka-inst',
 'sub_dataset_name': '-',
 'task_type': 'question-answering',
 'template_id': 3,
 'language': 'eng',
 'split': 'train',
 'script': 'Latn'
}

Data Fields

The data fields are the same among all splits:

  • id: Unique id of the data point
  • inputs: Prompt or input to the language model.
  • targets: Completion or output of the language model.
  • dataset_name: The name of the source dataset that the data point was taken from
  • sub_dataset_name: If the source is a collection, this field indicates which part of that collection the data point was taken from. If it is not a collection, this field is left blank.
  • task_type: The task type that this conversation belongs to.
  • template_id: The id of the template applied to this data point.
  • language: The ISO code of the dialect of the conversation.
  • script: The script of the language.
  • split: Indicates whether the data point is part of the train or the test split.

Statistics

The total number of data points, including the Aya Dataset` is 513,758,189. To view the breakdown of dialect codes and the respective templated and translated data point counts in the Aya Collection , refer to the toggled table below.

Breakdown of Aya Collection data point counts grouped by dialects
dialect code language total count
ace Achinese 8242684
acm Arabic 4120342
acq Arabic 4120342
aeb Arabic 4120342
afr Afrikaans 4126450
ajp Arabic 4120342
als Albanian 4120342
amh Amharic 4145669
apc Arabic 4120342
arb Arabic 6641429
ars Arabic 4120342
ary Arabic 4138418
arz Arabic 4120342
azb Azerbaijani 4120342
azj Azerbaijani 4120342
bel Belarusian 4141615
ben Bengali 4151003
bjn Banjar 8242684
bul Bulgarian 4158064
cat Catalan 4187242
ceb Cebuano 4120342
ces Czech 4299946
ckb Kurdish 4120342
cym Welsh 4120342
dan Danish 4156652
deu German 5447064
ell Greek 4160633
eng English 17838105
epo Esperanto 4120342
est Estonian 4120342
eus Basque 4120342
fin Finnish 4578237
fra French 4955862
gla Scottish Gaelic 4120342
gle Irish 4120342
glg Galician 4120342
guj Gujarati 4122499
hat Haitian Creole 4120342
hau Hausa 4171738
heb Hebrew 4223808
hin Hindi 4380729
hun Hungarian 4202381
hye Armenian 4127422
ibo Igbo 4156654
ind Indonesian 4166051
isl Icelandic 4120342
ita Italian 4526024
jav Javanese 4121171
jpn Japanese 6813519
kan Kannada 4121498
kas Kashmiri 4120342
kat Georgian 4120342
kaz Kazakh 4120342
khk Mongolian 4120342
khm Khmer 4120342
kir Kyrgyz 4120342
kmr Kurdish 4120342
knc Kanuri 8240684
kor Korean 4161353
lao Lao 4120342
lit Lithuanian 4120342
ltz Luxembourgish 4120342
lvs Latvian 4120342
mal Malayalam 4124689
mar Marathi 4124020
min Minangkabau 6755788
mkd Macedonian 4120342
mlt Maltese 4120342
mni Manipuri 4120342
mri Maori 4120342
mya Burmese 4120342
nld Dutch 4340523
nno Norwegian 4120342
nob Norwegian 4120342
npi Nepali 4120342
nso Northern Sotho 4120342
pbt Pashto 4120342
pes Persian 4365862
plt Malagasy 4120342
pol Polish 4452845
por Portuguese 4407774
ron Romanian 4156701
rus Russian 4666262
sin Sinhala 4120537
slk Slovak 4148187
slv Slovenian 4146073
smo Samoan 4120342
sna Shona 4124026
snd Sindhi 4120342
som Somali 4123268
sot Southern Sotho 4120342
spa Spanish 4499536
srp Serbian 4197466
sun Sundanese 4122550
swe Swedish 4196828
swh Swahili 4133068
tam Tamil 4131804
taq Tamasheq 4120342
tel Telugu 4598163
tgk Tajik 4120342
tha Thai 6245522
tur Turkish 4180274
ukr Ukrainian 4309726
urd Urdu 4458081
uzn Uzbek 4120342
vie Vietnamese 4162574
xho Xhosa 4123294
ydd Yiddish 4120342
yor Yoruba 4125249
yue Chinese 4120342
zho-Hans Chinese 4174870
zho-Hant Chinese 4120342
zsm Malay 4134292
zul Zulu 4121128
arq Arabic 6046
ban Balinese 2000
bbc Toba Batak 2000
bem Bemba 776
fil Filipino 220
fon Fon 845
hrv Croatian 9007
kin Kinyarwanda 11165
lij Ligurian 6409
mad Madurese 2000
nij Ngaju 2000
nor Norwegian 72352
pan Punjabi 2156
twi Twi 10840
wol Wolof 785
zho Chinese 74972

PS: Templated data also includes Mozambican Portuguese, which doesn't have its own ISO language code.


Motivations & Intentions

  • Curation Rationale: Automatic augmentation of existing datasets serves to enhance the available linguistic resources for multiple languages. The list of languages was initially established from mT5 and aligned with the annotators’ language list and NLLB translation model. The datasets were translated directly from English for all languages.

Additional Information

Provenance

  • Methods Used: A combination of crowd-sourced templating and automatic translation was employed to source this dataset.
  • Methodology Details:
    • Source: Existing NLP datasets
    • Dates of Collection: May 2023 - Dec 2023

Dataset Version and Maintenance

  • Maintenance Status: Actively Maintained
  • Version Details:
    • Current version: 1.0
    • Last Update: 02/2024
    • First Release: 02/2024

Authorship

Licensing Information

This dataset can be used for any purpose, whether academic or commercial, under the terms of the Apache 2.0 License.

Citation Information

@misc{singh2024aya,
      title={Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning}, 
      author={Shivalika Singh and Freddie Vargus and Daniel Dsouza and Börje F. Karlsson and Abinaya Mahendiran and Wei-Yin Ko and Herumb Shandilya and Jay Patel and Deividas Mataciunas and Laura OMahony and Mike Zhang and Ramith Hettiarachchi and Joseph Wilson and Marina Machado and Luisa Souza Moura and Dominik Krzemiński and Hakimeh Fadaei and Irem Ergün and Ifeoma Okoh and Aisha Alaagib and Oshan Mudannayake and Zaid Alyafeai and Vu Minh Chien and Sebastian Ruder and Surya Guthikonda and Emad A. Alghamdi and Sebastian Gehrmann and Niklas Muennighoff and Max Bartolo and Julia Kreutzer and Ahmet Üstün and Marzieh Fadaee and Sara Hooker},
      year={2024},
      eprint={2402.06619},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
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