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---
language:
- ar
task_categories:
- conversational
- text-generation
- text2text-generation
- translation
- summarization
pretty_name: MAD
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: GenId
dtype: int64
- name: SubId
dtype: int64
- name: DatasetName
dtype: string
- name: DatasetLink
dtype: string
- name: Text
dtype: string
- name: MetaData
struct:
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dtype: string
- name: AboutBook
dtype: string
- name: Author
dtype: string
- name: AuthorName
dtype: string
- name: BookLink
dtype: string
- name: BookName
dtype: string
- name: ChapterLink
dtype: string
- name: ChapterName
dtype: string
- name: Tags
dtype: float64
- name: __index_level_0__
dtype: float64
- name: created_date
dtype: string
- name: deleted
dtype: bool
- name: detoxify
dtype: 'null'
- name: emojis
struct:
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sequence: int32
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sequence: string
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dtype: string
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struct:
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sequence: int32
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sequence: string
- name: value
sequence: float64
- name: lang
dtype: string
- name: message_id
dtype: string
- name: message_tree_id
dtype: string
- name: model_name
dtype: 'null'
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dtype: string
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dtype: float64
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dtype: string
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dtype: float64
- name: review_result
dtype: bool
- name: role
dtype: string
- name: synthetic
dtype: bool
- name: title
dtype: string
- name: tree_state
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: verses_keys
dtype: string
- name: ConcatenatedText
dtype: int64
- name: __index_level_0__
dtype: float64
splits:
- name: train
num_bytes: 2121243070
num_examples: 187510
download_size: 841102063
dataset_size: 2121243070
---
# Dataset Card for "Mixed-Arabic-Dataset"
## Mixed Arabic Datasets (MAD)
The Mixed Arabic Datasets (MAD) project provides a comprehensive collection of diverse Arabic-language datasets, sourced from various repositories, platforms, and domains. These datasets cover a wide range of text types, including books, articles, Wikipedia content, stories, and more.
### MAD Repo vs. MAD Main
#### MAD Repo
- **Versatility**: In the MAD Repository (MAD Repo), datasets are made available in their original, native form. Researchers and practitioners can selectively download specific datasets that align with their specific interests or requirements.
- **Independent Access**: Each dataset is self-contained, enabling users to work with individual datasets independently, allowing for focused analyses and experiments.
#### MAD Main or simply MAD
- **Unified Dataframe**: MAD Main represents a harmonized and unified dataframe, incorporating all datasets from the MAD Repository. It provides a seamless and consolidated view of the entire MAD collection, making it convenient for comprehensive analyses and applications.
- **Holistic Perspective**: Researchers can access a broad spectrum of Arabic-language content within a single dataframe, promoting holistic exploration and insights across diverse text sources.
### Why MAD Main?
- **Efficiency**: Working with MAD Main streamlines the data acquisition process by consolidating multiple datasets into one structured dataframe. This is particularly beneficial for large-scale projects or studies requiring diverse data sources.
- **Interoperability**: With MAD Main, the datasets are integrated into a standardized format, enhancing interoperability and compatibility with a wide range of data processing and analysis tools.
- **Meta-Analysis**: Researchers can conduct comprehensive analyses, such as cross-domain studies, trend analyses, or comparative studies, by leveraging the combined richness of all MAD datasets.
### Getting Started
- To access individual datasets in their original form, refer to the MAD Repository ([Link to MAD Repo](https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Datasets-Repo)).
- For a unified view of all datasets, conveniently organized in a dataframe, you are here in the right place.
```python
from datasets import load_dataset
dataset = load_dataset("M-A-D/Mixed-Arabic-Dataset-Main")
```
### Join Us on Discord
For discussions, contributions, and community interactions, join us on Discord! [](https://discord.gg/2NpJ9JGm)
### 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](https://colab.research.google.com/drive/1w7_7lL6w7nM9DcDmTZe1Vfiwkio6SA-w?usp=sharing).
**Note**: If you'd like to test a contribution before submitting it, feel free to do so on the [MAD Test Dataset](https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Dataset-test).
## 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},
}
``` |