language:
- ar
size_categories:
- 1B<n<10B
task_categories:
- text-classification
- question-answering
- translation
- summarization
- conversational
- text-generation
- text2text-generation
- fill-mask
pretty_name: Mixed Arabic Datasets (MAD) Corpus
dataset_info:
- config_name: Ara--Abdelaziz--MNAD.v1
features:
- name: Title
dtype: string
- name: Body
dtype: string
- name: Category
dtype: string
splits:
- name: train
num_bytes: 1101921980
num_examples: 418563
download_size: 526103216
dataset_size: 1101921980
- config_name: Ara--Abdelaziz--QuranExe
features:
- name: text
dtype: string
- name: resource_name
dtype: string
- name: verses_keys
dtype: string
splits:
- name: train
num_bytes: 133108687
num_examples: 49888
download_size: 58769326
dataset_size: 133108687
- config_name: Ara--Abdelaziz--tweet_sentiment_multilingual
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 306108
num_examples: 1839
download_size: 172509
dataset_size: 306108
- config_name: Ara--Ali-C137--Hindawi-Books-dataset
features:
- name: BookLink
dtype: string
- name: BookName
dtype: string
- name: AuthorName
dtype: string
- name: AboutBook
dtype: string
- name: ChapterLink
dtype: string
- name: ChapterName
dtype: string
- name: ChapterText
dtype: string
- name: AboutAuthor
dtype: string
splits:
- name: train
num_bytes: 1364854259
num_examples: 49821
download_size: 494678002
dataset_size: 1364854259
- config_name: Ara--Goud--Goud-sum
features:
- name: article
dtype: string
- name: headline
dtype: string
- name: categories
dtype: string
splits:
- name: train
num_bytes: 288296544
num_examples: 139288
download_size: 147735776
dataset_size: 288296544
- config_name: Ara--J-Mourad--MNAD.v1
features:
- name: Title
dtype: string
- name: Body
dtype: string
- name: Category
dtype: string
splits:
- name: train
num_bytes: 1101921980
num_examples: 418563
download_size: 0
dataset_size: 1101921980
- config_name: Ara--JihadZa--IADD
features:
- name: Sentence
dtype: string
- name: Region
dtype: string
- name: DataSource
dtype: string
- name: Country
dtype: string
splits:
- name: train
num_bytes: 19167070
num_examples: 135804
download_size: 8644491
dataset_size: 19167070
- config_name: Ara--LeMGarouani--MAC-corpus
features:
- name: tweets
dtype: string
- name: type
dtype: string
- name: class
dtype: string
splits:
- name: train
num_bytes: 1945646
num_examples: 18087
download_size: 866198
dataset_size: 1945646
- config_name: Ara--MBZUAI--Bactrian-X
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: id
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 66093524
num_examples: 67017
download_size: 33063779
dataset_size: 66093524
- config_name: Ara--OpenAssistant--oasst1
features:
- name: message_id
dtype: string
- name: parent_id
dtype: string
- name: user_id
dtype: string
- name: created_date
dtype: string
- name: text
dtype: string
- name: role
dtype: string
- name: lang
dtype: string
- name: review_count
dtype: int32
- name: review_result
dtype: bool
- name: deleted
dtype: bool
- name: rank
dtype: float64
- name: synthetic
dtype: bool
- name: model_name
dtype: 'null'
- name: detoxify
dtype: 'null'
- name: message_tree_id
dtype: string
- name: tree_state
dtype: string
- name: emojis
struct:
- name: count
sequence: int32
- name: name
sequence: string
- name: labels
struct:
- name: count
sequence: int32
- name: name
sequence: string
- name: value
sequence: float64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 58168
num_examples: 56
download_size: 30984
dataset_size: 58168
- config_name: Ara--Wikipedia
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 3052201469
num_examples: 1205403
download_size: 1316212231
dataset_size: 3052201469
- config_name: Ara--miracl--miracl
features:
- name: query_id
dtype: string
- name: query
dtype: string
- name: positive_passages
list:
- name: docid
dtype: string
- name: text
dtype: string
- name: title
dtype: string
- name: negative_passages
list:
- name: docid
dtype: string
- name: text
dtype: string
- name: title
dtype: string
splits:
- name: train
num_bytes: 32012083
num_examples: 3495
download_size: 15798509
dataset_size: 32012083
- config_name: Ara--mustapha--QuranExe
features:
- name: text
dtype: string
- name: resource_name
dtype: string
- name: verses_keys
dtype: string
splits:
- name: train
num_bytes: 133108687
num_examples: 49888
download_size: 58769417
dataset_size: 133108687
- config_name: Ara--pain--Arabic-Tweets
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 41639770853
num_examples: 202700438
download_size: 22561651700
dataset_size: 41639770853
- config_name: Ara--saudinewsnet
features:
- name: source
dtype: string
- name: url
dtype: string
- name: date_extracted
dtype: string
- name: title
dtype: string
- name: author
dtype: string
- name: content
dtype: string
splits:
- name: train
num_bytes: 103654009
num_examples: 31030
download_size: 49117164
dataset_size: 103654009
- config_name: Ary--AbderrahmanSkiredj1--Darija-Wikipedia
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 8104410
num_examples: 4862
download_size: 3229966
dataset_size: 8104410
- config_name: Ary--Ali-C137--Darija-Stories-Dataset
features:
- name: ChapterName
dtype: string
- name: ChapterLink
dtype: string
- name: Author
dtype: string
- name: Text
dtype: string
- name: Tags
dtype: int64
splits:
- name: train
num_bytes: 476926644
num_examples: 6142
download_size: 241528641
dataset_size: 476926644
- config_name: Ary--Wikipedia
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 10007364
num_examples: 6703
download_size: 4094377
dataset_size: 10007364
- config_name: Arz--Wikipedia
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 1364641408
num_examples: 1617770
download_size: 306420318
dataset_size: 1364641408
configs:
- config_name: Ara--Abdelaziz--MNAD.v1
data_files:
- split: train
path: Ara--Abdelaziz--MNAD.v1/train-*
- config_name: Ara--Abdelaziz--QuranExe
data_files:
- split: train
path: Ara--Abdelaziz--QuranExe/train-*
- config_name: Ara--Abdelaziz--tweet_sentiment_multilingual
data_files:
- split: train
path: Ara--Abdelaziz--tweet_sentiment_multilingual/train-*
- config_name: Ara--Ali-C137--Hindawi-Books-dataset
data_files:
- split: train
path: Ara--Ali-C137--Hindawi-Books-dataset/train-*
- config_name: Ara--Goud--Goud-sum
data_files:
- split: train
path: Ara--Goud--Goud-sum/train-*
- config_name: Ara--J-Mourad--MNAD.v1
data_files:
- split: train
path: Ara--J-Mourad--MNAD.v1/train-*
- config_name: Ara--JihadZa--IADD
data_files:
- split: train
path: Ara--JihadZa--IADD/train-*
- config_name: Ara--LeMGarouani--MAC-corpus
data_files:
- split: train
path: Ara--LeMGarouani--MAC-corpus/train-*
- config_name: Ara--MBZUAI--Bactrian-X
data_files:
- split: train
path: Ara--MBZUAI--Bactrian-X/train-*
- config_name: Ara--OpenAssistant--oasst1
data_files:
- split: train
path: Ara--OpenAssistant--oasst1/train-*
- config_name: Ara--Wikipedia
data_files:
- split: train
path: Ara--Wikipedia/train-*
- config_name: Ara--miracl--miracl
data_files:
- split: train
path: Ara--miracl--miracl/train-*
- config_name: Ara--mustapha--QuranExe
data_files:
- split: train
path: Ara--mustapha--QuranExe/train-*
- config_name: Ara--pain--Arabic-Tweets
data_files:
- split: train
path: Ara--pain--Arabic-Tweets/train-*
- config_name: Ara--saudinewsnet
data_files:
- split: train
path: Ara--saudinewsnet/train-*
- config_name: Ary--AbderrahmanSkiredj1--Darija-Wikipedia
data_files:
- split: train
path: Ary--AbderrahmanSkiredj1--Darija-Wikipedia/train-*
- config_name: Ary--Ali-C137--Darija-Stories-Dataset
data_files:
- split: train
path: Ary--Ali-C137--Darija-Stories-Dataset/train-*
- config_name: Ary--Wikipedia
data_files:
- split: train
path: Ary--Wikipedia/train-*
- config_name: Arz--Wikipedia
data_files:
- split: train
path: Arz--Wikipedia/train-*
Dataset Card for "Mixed Arabic Datasets (MAD) Corpus"
The Mixed Arabic Datasets Corpus : A Community-Driven Collection of Diverse Arabic Texts
Dataset Description
The Mixed Arabic Datasets (MAD) presents a dynamic compilation of diverse Arabic texts sourced from various online platforms and datasets. It addresses a critical challenge faced by researchers, linguists, and language enthusiasts: the fragmentation of Arabic language datasets across the Internet. With MAD, we are trying to centralize these dispersed resources into a single, comprehensive repository.
Encompassing a wide spectrum of content, ranging from social media conversations to literary masterpieces, MAD captures the rich tapestry of Arabic communication, including both standard Arabic and regional dialects.
This corpus offers comprehensive insights into the linguistic diversity and cultural nuances of Arabic expression.
Usage
If you want to use this dataset you pick one among the available configs:
Ara--MBZUAI--Bactrian-X | Ara--OpenAssistant--oasst1 | Ary--AbderrahmanSkiredj1--Darija-Wikipedia
Ara--Wikipedia | Ary--Wikipedia | Arz--Wikipedia
Ary--Ali-C137--Darija-Stories-Dataset | Ara--Ali-C137--Hindawi-Books-dataset | ``
Example of usage:
dataset = load_dataset('M-A-D/Mixed-Arabic-Datasets-Repo', 'Ara--MBZUAI--Bactrian-X')
If you loaded multiple datasets and wanted to merge them together then you can simply laverage concatenate_datasets() from datasets
dataset3 = concatenate_datasets([dataset1['train'], dataset2['train']])
Note : proccess the datasets before merging in order to make sure you have a new dataset that is consistent
Dataset Size
The Mixed Arabic Datasets (MAD) is a dynamic and evolving collection, with its size fluctuating as new datasets are added or removed. As MAD continuously expands, it becomes a living resource that adapts to the ever-changing landscape of Arabic language datasets.
Dataset List
MAD draws from a diverse array of sources, each contributing to its richness and breadth. While the collection is constantly evolving, some of the datasets that are poised to join MAD in the near future include:
- [✔] OpenAssistant/oasst1 (ar portion) : Dataset Link
- [✔] MBZUAI/Bactrian-X (ar portion) : Dataset Link
- [✔] AbderrahmanSkiredj1/Darija-Wikipedia : Dataset Link
- [✔] Arabic Wikipedia : Dataset Link
- [✔] Moroccan Arabic Wikipedia : Dataset Link
- [✔] Egyptian Arabic Wikipedia : Dataset Link
- [✔] Darija Stories Dataset : Dataset Link
- [✔] Hindawi Books Dataset : Dataset Link
- [] uonlp/CulturaX - ar : Dataset Link
- [] Pain/ArabicTweets : Dataset Link
- [] Abu-El-Khair Corpus : Dataset Link
- [✔] QuranExe : Dataset Link
- [✔] MNAD : Dataset Link
- [] IADD : Dataset Link
- [] OSIAN : Dataset Link
- [] MAC corpus : Dataset Link
- [✔] Goud.ma-Sum : Dataset Link
- [✔] SaudiNewsNet : Dataset Link
- [✔] Miracl : Dataset Link
- [✔] CardiffNLP/TweetSentimentMulti : Dataset Link
- [] OSCAR-2301 : Dataset Link
- [] mc4 : Dataset Link
- [] Muennighoff/xP3x : Dataset Link
- [] Ai_Society : Dataset Link
Potential Use Cases
The Mixed Arabic Datasets (MAD) holds the potential to catalyze a multitude of groundbreaking applications:
- Linguistic Analysis: Employ MAD to conduct in-depth linguistic studies, exploring dialectal variances, language evolution, and grammatical structures.
- Topic Modeling: Dive into diverse themes and subjects through the extensive collection, revealing insights into emerging trends and prevalent topics.
- Sentiment Understanding: Decode sentiments spanning Arabic dialects, revealing cultural nuances and emotional dynamics.
- Sociocultural Research: Embark on a sociolinguistic journey, unraveling the intricate connection between language, culture, and societal shifts.
Dataset Access
MAD's access mechanism is unique: while it doesn't carry a general license itself, each constituent dataset within the corpus retains its individual license. By accessing the dataset details through the provided links in the "Dataset List" section above, users can understand the specific licensing terms for each dataset.
Join Us on Discord
For discussions, contributions, and community interactions, join us on Discord!
How to Contribute
Want to contribute to the Mixed Arabic Datasets project? Follow our comprehensive guide on Google Colab for step-by-step instructions: Contribution Guide.
Note: If you'd like to test a contribution before submitting it, feel free to do so on the MAD Test Dataset.
Citation
@dataset{
title = {Mixed Arabic Datasets (MAD)},
author = {MAD Community},
howpublished = {Dataset},
url = {https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Datasets-Repo},
year = {2023},
}