Arabic_Aya / README.md
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metadata
language:
  - ar
license: apache-2.0
size_categories:
  - 1M<n<10M
task_categories:
  - text-classification
  - translation
  - summarization
pretty_name: 2A
dataset_info:
  - config_name: CohereForAI-aya_collection-aya_dataset
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  - config_name: CohereForAI-aya_collection-aya_human_annotated
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  - config_name: CohereForAI-aya_collection-templated_afrisenti
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  - config_name: CohereForAI-aya_collection-templated_mintaka
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  - config_name: CohereForAI-aya_collection-templated_ntx_llm
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  - config_name: CohereForAI-aya_collection-templated_xcsqa
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  - config_name: CohereForAI-aya_collection-templated_xlel_wd
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  - config_name: CohereForAI-aya_collection-translated_adversarial_qa
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  - config_name: CohereForAI-aya_collection-translated_cnn_dailymail
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  - config_name: CohereForAI-aya_collection-translated_dolly
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  - config_name: CohereForAI-aya_collection-translated_flan_coqa
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  - config_name: CohereForAI-aya_collection-translated_flan_cot
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  - config_name: CohereForAI-aya_collection-translated_flan_gem_wiki
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  - config_name: CohereForAI-aya_collection-translated_flan_lambada
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  - config_name: CohereForAI-aya_collection-translated_flan_qa
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  - config_name: CohereForAI-aya_collection-translated_hotpotqa
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  - config_name: CohereForAI-aya_collection-translated_joke_explaination
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  - config_name: CohereForAI-aya_collection-translated_mintaka
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  - config_name: CohereForAI-aya_collection-translated_mlqa
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  - config_name: CohereForAI-aya_collection-translated_nqopen
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  - config_name: CohereForAI-aya_collection-translated_paws
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  - config_name: CohereForAI-aya_collection-translated_soda
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  - config_name: CohereForAI-aya_collection-translated_wiki_split
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  - config_name: CohereForAI-aya_collection-translated_wikiqa
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  - config_name: CohereForAI-aya_collection-translated_xlel_wd
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  - config_name: CohereForAI-aya_dataset
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  - config_name: CohereForAI-aya_evaluation_suite-aya_human_annotated
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  - config_name: CohereForAI-aya_evaluation_suite-dolly_human_edited
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  - config_name: CohereForAI-aya_evaluation_suite-dolly_machine_translated
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configs:
  - config_name: CohereForAI-aya_collection-aya_dataset
    data_files:
      - split: train
        path: CohereForAI-aya_collection-aya_dataset/train-*
  - config_name: CohereForAI-aya_collection-aya_human_annotated
    data_files:
      - split: test
        path: CohereForAI-aya_collection-aya_human_annotated/test-*
  - config_name: CohereForAI-aya_collection-templated_afrisenti
    data_files:
      - split: train
        path: CohereForAI-aya_collection-templated_afrisenti/train-*
      - split: test
        path: CohereForAI-aya_collection-templated_afrisenti/test-*
      - split: validation
        path: CohereForAI-aya_collection-templated_afrisenti/validation-*
  - config_name: CohereForAI-aya_collection-templated_mintaka
    data_files:
      - split: train
        path: CohereForAI-aya_collection-templated_mintaka/train-*
      - split: test
        path: CohereForAI-aya_collection-templated_mintaka/test-*
      - split: validation
        path: CohereForAI-aya_collection-templated_mintaka/validation-*
  - config_name: CohereForAI-aya_collection-templated_ntx_llm
    data_files:
      - split: train
        path: CohereForAI-aya_collection-templated_ntx_llm/train-*
  - config_name: CohereForAI-aya_collection-templated_xcsqa
    data_files:
      - split: validation
        path: CohereForAI-aya_collection-templated_xcsqa/validation-*
  - config_name: CohereForAI-aya_collection-templated_xlel_wd
    data_files:
      - split: train
        path: CohereForAI-aya_collection-templated_xlel_wd/train-*
      - split: test
        path: CohereForAI-aya_collection-templated_xlel_wd/test-*
      - split: validation
        path: CohereForAI-aya_collection-templated_xlel_wd/validation-*
  - config_name: CohereForAI-aya_collection-translated_adversarial_qa
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_adversarial_qa/train-*
      - split: test
        path: CohereForAI-aya_collection-translated_adversarial_qa/test-*
      - split: validation
        path: CohereForAI-aya_collection-translated_adversarial_qa/validation-*
  - config_name: CohereForAI-aya_collection-translated_cnn_dailymail
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_cnn_dailymail/train-*
      - split: test
        path: CohereForAI-aya_collection-translated_cnn_dailymail/test-*
      - split: validation
        path: CohereForAI-aya_collection-translated_cnn_dailymail/validation-*
  - config_name: CohereForAI-aya_collection-translated_dolly
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_dolly/train-*
  - config_name: CohereForAI-aya_collection-translated_flan_coqa
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_flan_coqa/train-*
  - config_name: CohereForAI-aya_collection-translated_flan_cot
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_flan_cot/train-*
  - config_name: CohereForAI-aya_collection-translated_flan_gem_wiki
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_flan_gem_wiki/train-*
  - config_name: CohereForAI-aya_collection-translated_flan_lambada
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_flan_lambada/train-*
  - config_name: CohereForAI-aya_collection-translated_flan_qa
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_flan_qa/train-*
  - config_name: CohereForAI-aya_collection-translated_hotpotqa
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_hotpotqa/train-*
      - split: validation
        path: CohereForAI-aya_collection-translated_hotpotqa/validation-*
  - config_name: CohereForAI-aya_collection-translated_joke_explaination
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_joke_explaination/train-*
  - config_name: CohereForAI-aya_collection-translated_mintaka
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_mintaka/train-*
      - split: test
        path: CohereForAI-aya_collection-translated_mintaka/test-*
      - split: validation
        path: CohereForAI-aya_collection-translated_mintaka/validation-*
  - config_name: CohereForAI-aya_collection-translated_mlqa
    data_files:
      - split: test
        path: CohereForAI-aya_collection-translated_mlqa/test-*
      - split: validation
        path: CohereForAI-aya_collection-translated_mlqa/validation-*
  - config_name: CohereForAI-aya_collection-translated_nqopen
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_nqopen/train-*
      - split: validation
        path: CohereForAI-aya_collection-translated_nqopen/validation-*
  - config_name: CohereForAI-aya_collection-translated_paws
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_paws/train-*
      - split: test
        path: CohereForAI-aya_collection-translated_paws/test-*
      - split: validation
        path: CohereForAI-aya_collection-translated_paws/validation-*
  - config_name: CohereForAI-aya_collection-translated_piqa
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_piqa/train-*
      - split: validation
        path: CohereForAI-aya_collection-translated_piqa/validation-*
  - config_name: CohereForAI-aya_collection-translated_soda
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_soda/train-*
      - split: test
        path: CohereForAI-aya_collection-translated_soda/test-*
      - split: validation
        path: CohereForAI-aya_collection-translated_soda/validation-*
  - config_name: CohereForAI-aya_collection-translated_wiki_split
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_wiki_split/train-*
      - split: test
        path: CohereForAI-aya_collection-translated_wiki_split/test-*
      - split: validation
        path: CohereForAI-aya_collection-translated_wiki_split/validation-*
  - config_name: CohereForAI-aya_collection-translated_wikiqa
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_wikiqa/train-*
      - split: test
        path: CohereForAI-aya_collection-translated_wikiqa/test-*
      - split: validation
        path: CohereForAI-aya_collection-translated_wikiqa/validation-*
  - config_name: CohereForAI-aya_collection-translated_xlel_wd
    data_files:
      - split: train
        path: CohereForAI-aya_collection-translated_xlel_wd/train-*
      - split: test
        path: CohereForAI-aya_collection-translated_xlel_wd/test-*
      - split: validation
        path: CohereForAI-aya_collection-translated_xlel_wd/validation-*
  - config_name: CohereForAI-aya_dataset
    data_files:
      - split: train
        path: CohereForAI-aya_dataset/train-*
      - split: test
        path: CohereForAI-aya_dataset/test-*
  - config_name: CohereForAI-aya_evaluation_suite-aya_human_annotated
    data_files:
      - split: test
        path: CohereForAI-aya_evaluation_suite-aya_human_annotated/test-*
  - config_name: CohereForAI-aya_evaluation_suite-dolly_human_edited
    data_files:
      - split: test
        path: CohereForAI-aya_evaluation_suite-dolly_human_edited/test-*
  - config_name: CohereForAI-aya_evaluation_suite-dolly_machine_translated
    data_files:
      - split: test
        path: CohereForAI-aya_evaluation_suite-dolly_machine_translated/test-*

Dataset Card for : Arabic Aya (2A)

Arabic Aya (2A) : A Curated Subset of the Aya Collection for Arabic Language Processing

Dataset Sources & Infos

Overview

Arabic Aya is a meticulously curated dataset derived from the comprehensive Aya collection by CohereForAI, specifically focusing on Arabic text data. This dataset aggregates content from the CohereForAI/aya_collection, CohereForAI/aya_dataset, and CohereForAI/aya_evaluation_suite, filtering out all but the Arabic content, including both Modern Standard Arabic (MSA) and various regional dialects.

Purpose

The aim of 'Arabic Aya' is to provide researchers, technologists, and linguists with a ready-to-use Arabic text resource, significantly reducing the time and effort required for data preprocessing in NLP and AI projects focused on the Arabic language.

  • Use the Aya datasets out of the box for your Arabic applications and research 😀

Usage

This dataset serves as a foundational tool for those embarking on Arabic language projects, from academic research to commercial applications. By providing a pre-filtered source of Arabic text, 'Arabic Aya' enables users to dive straight into model training, analysis, and application development without the preliminary hassle of data cleaning and language filtering.

Use with HuggingFace's datasets library

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

from datasets import load_dataset

dataset = load_dataset("2A2I/Arabic_Aya", "CohereForAI-aya_collection-templated_mintaka")

In the above code snippet, "CohereForAI-aya_collection-templated_mintaka" refers to the arabic version (100k rows) of the original "templated_mintaka" subset (780k rows) of the aya_collection. You can load other subsets by specifying its name at the time of loading the dataset.

Access and Contribution

Available on the Hugging Face Hub under 2A2I/Arabic_Aya, 'Arabic Aya' invites contributions from the community. Users are encouraged to offer feedback, suggest improvements.

Support and Collaboration

We are committed to fostering an inclusive and supportive environment around Arabic AI and NLP research. For support, collaboration, or queries regarding the dataset, please reach out through the Hugging Face Hub's discussion section or reach out at 2A2I Contact Email.

Original Dataset Card of Aya by CohereForAI

Aya Header

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.
    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.

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("CohereForAI/aya_collection", "templated_mintaka")

In the above code snippet, "templated_mintaka" 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 translated data point count templated data point count total count
ace Achinese 8240684 2000 8242684
acm Arabic 4120342 0 4120342
acq Arabic 4120342 0 4120342
aeb Arabic 4120342 0 4120342
afr Afrikaans 4120342 6108 4126450
ajp Arabic 4120342 0 4120342
als Albanian 4120342 0 4120342
amh Amharic 4120342 25327 4145669
apc Arabic 4120342 0 4120342
arb Arabic 6424999 216430 6641429
ars Arabic 4120342 0 4120342
ary Arabic 4120342 18076 4138418
arz Arabic 4120342 0 4120342
azb Azerbaijani 4120342 0 4120342
azj Azerbaijani 4120342 0 4120342
bel Belarusian 4120342 21273 4141615
ben Bengali 4120342 30661 4151003
bjn Banjar 8240684 2000 8242684
bul Bulgarian 4120342 37722 4158064
cat Catalan 4120342 66900 4187242
ceb Cebuano 4120342 0 4120342
ces Czech 4120342 179604 4299946
ckb Kurdish 4120342 0 4120342
cym Welsh 4120342 0 4120342
dan Danish 4120342 36310 4156652
deu German 4120342 1326722 5447064
ell Greek 4120342 40291 4160633
eng English 9771427 8066678 17838105
epo Esperanto 4120342 0 4120342
est Estonian 4120342 0 4120342
eus Basque 4120342 0 4120342
fin Finnish 4120342 457895 4578237
fra French 4120342 835520 4955862
gla Scottish Gaelic 4120342 0 4120342
gle Irish 4120342 0 4120342
glg Galician 4120342 0 4120342
guj Gujarati 4120342 2157 4122499
hat Haitian Creole 4120342 0 4120342
hau Hausa 4120342 51396 4171738
heb Hebrew 4120342 103466 4223808
hin Hindi 4120342 260387 4380729
hun Hungarian 4120342 82039 4202381
hye Armenian 4120342 7080 4127422
ibo Igbo 4120342 36312 4156654
ind Indonesian 4120342 45709 4166051
isl Icelandic 4120342 0 4120342
ita Italian 4120342 405682 4526024
jav Javanese 4120342 829 4121171
jpn Japanese 4120342 2693177 6813519
kan Kannada 4120342 1156 4121498
kas Kashmiri 4120342 0 4120342
kat Georgian 4120342 0 4120342
kaz Kazakh 4120342 0 4120342
khk Mongolian 4120342 0 4120342
khm Khmer 4120342 0 4120342
kir Kyrgyz 4120342 0 4120342
kmr Kurdish 4120342 0 4120342
knc Kanuri 8240684 0 8240684
kor Korean 4120342 41011 4161353
lao Lao 4120342 0 4120342
lit Lithuanian 4120342 0 4120342
ltz Luxembourgish 4120342 0 4120342
lvs Latvian 4120342 0 4120342
mal Malayalam 4120342 4347 4124689
mar Marathi 4120342 3678 4124020
min Minangkabau 6753788 2000 6755788
mkd Macedonian 4120342 0 4120342
mlt Maltese 4120342 0 4120342
mni Manipuri 4120342 0 4120342
mri Maori 4120342 0 4120342
mya Burmese 4120342 0 4120342
nld Dutch 4120342 220181 4340523
nno Norwegian 4120342 0 4120342
nob Norwegian 4120342 0 4120342
npi Nepali 4120342 0 4120342
nso Northern Sotho 4120342 0 4120342
pbt Pashto 4120342 0 4120342
pes Persian 4120342 245520 4365862
plt Malagasy 4120342 0 4120342
pol Polish 4120342 332503 4452845
por Portuguese 4120342 287432 4407774
ron Romanian 4120342 36359 4156701
rus Russian 4120342 545920 4666262
sin Sinhala 4120342 195 4120537
slk Slovak 4120342 27845 4148187
slv Slovenian 4120342 25731 4146073
smo Samoan 4120342 0 4120342
sna Shona 4120342 3684 4124026
snd Sindhi 4120342 0 4120342
som Somali 4120342 2926 4123268
sot Southern Sotho 4120342 0 4120342
spa Spanish 4120342 379194 4499536
srp Serbian 4120342 77124 4197466
sun Sundanese 4120342 2208 4122550
swe Swedish 4120342 76486 4196828
swh Swahili 4120342 12726 4133068
tam Tamil 4120342 11462 4131804
taq Tamasheq 4120342 0 4120342
tel Telugu 4120342 477821 4598163
tgk Tajik 4120342 0 4120342
tha Thai 4120342 2125180 6245522
tur Turkish 4120342 59932 4180274
ukr Ukrainian 4120342 189384 4309726
urd Urdu 4120342 337739 4458081
uzn Uzbek 4120342 0 4120342
vie Vietnamese 4120342 42232 4162574
xho Xhosa 4120342 2952 4123294
ydd Yiddish 4120342 0 4120342
yor Yoruba 4120342 4907 4125249
yue Chinese 4120342 0 4120342
zho-Hans Chinese 4120342 54528 4174870
zho-Hant Chinese 4120342 0 4120342
zsm Malay 4120342 13950 4134292
zul Zulu 4120342 786 4121128
arq Arabic 0 6046 6046
ban Balinese 0 2000 2000
bbc Toba Batak 0 2000 2000
bem Bemba 0 776 776
fil Filipino 0 220 220
fon Fon 0 845 845
hrv Croatian 0 9007 9007
kin Kinyarwanda 0 11165 11165
lij Ligurian 0 6409 6409
mad Madurese 0 2000 2000
nij Ngaju 0 2000 2000
nor Norwegian 0 72352 72352
pan Punjabi 0 2156 2156
twi Twi 0 10840 10840
wol Wolof 0 785 785
zho Chinese 0 74972 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}
}