dataset_info:
- 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: Ary--AbderrahmanSkiredj1--Darija-Wikipedia
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 8104410
num_examples: 4862
download_size: 3229966
dataset_size: 8104410
configs:
- 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: Ary--AbderrahmanSkiredj1--Darija-Wikipedia
data_files:
- split: train
path: Ary--AbderrahmanSkiredj1--Darija-Wikipedia/train-*
language:
- ar
pretty_name: Mixed Arabic Datasets (MAD) Corpus
size_categories:
- 1B<n<10B
task_categories:
- text-classification
- question-answering
- translation
- summarization
- conversational
- text-generation
- text2text-generation
- fill-mask
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']
Example of usage:
dataset = load_dataset('mixed-arabic-datasets', '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 Details
- Homepage: https://huggingface.co/datasets/Ali-C137/Mixed-Arabic-Datasets
- Author: Elfilali Ali
- Email: ali.elfilali00@gmail.com, alielfilali0909@gmail.com
- GitHub Profile: https://github.com/alielfilali01
- LinkedIn Profile: https://www.linkedin.com/in/alielfilali01/
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
- [] 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
- [] Hindawi-Books-dataset : Dataset Link
- [] Miracl : Dataset Link
- [] CardiffNLP/TweetSentimentMulti : Dataset Link
- [] OSCAR-2301 : Dataset Link
- [] mc4 : Dataset Link
- [] Wikipedia : 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.
Citation
Showcase your commitment to collaboration and linguistic exploration by referencing the MAD collection in your research:
@dataset{
title = {Mixed Arabic Datasets (MAD)},
author = {Elfilali Ali},
howpublished = {Dataset},
url = {https://huggingface.co/datasets/Ali-C137/Mixed-Arabic-Datasets},
year = {2023},
}