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num_examples: 127898
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download_size: 774823370
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dataset_size: 1955979492
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---
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# Dataset Card for "Mixed-Arabic-Dataset
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[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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num_examples: 127898
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download_size: 774823370
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dataset_size: 1955979492
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task_categories:
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- conversational
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- text-generation
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- text2text-generation
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- translation
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- summarization
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language:
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- ar
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pretty_name: MAD
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---
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# Dataset Card for "Mixed-Arabic-Dataset"
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## Mixed Arabic Datasets (MAD)
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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.
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### MAD Repo vs. MAD Main
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#### MAD Repo
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- **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.
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- **Independent Access**: Each dataset is self-contained, enabling users to work with individual datasets independently, allowing for focused analyses and experiments.
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#### MAD Main or simply MAD
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- **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.
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- **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.
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### Why MAD Main?
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- **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.
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- **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.
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- **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.
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### Getting Started
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- 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)).
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- For a unified view of all datasets, conveniently organized in a dataframe, you are here in the right place.
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