|
--- |
|
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: |
|
- name: AboutAuthor |
|
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: |
|
- name: count |
|
sequence: int32 |
|
- name: name |
|
sequence: string |
|
- name: id |
|
dtype: string |
|
- name: labels |
|
struct: |
|
- name: count |
|
sequence: int32 |
|
- name: name |
|
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' |
|
- name: parent_id |
|
dtype: string |
|
- name: query_id |
|
dtype: string |
|
- name: rank |
|
dtype: float64 |
|
- name: review_count |
|
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: ConcatenatedText |
|
dtype: int64 |
|
- name: __index_level_0__ |
|
dtype: float64 |
|
splits: |
|
- name: train |
|
num_bytes: 1990497610 |
|
num_examples: 131393 |
|
download_size: 790648134 |
|
dataset_size: 1990497610 |
|
--- |
|
# 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! [![Discord](https://img.shields.io/discord/798499298231726101?label=Join%20us%20on%20Discord&logo=discord&logoColor=white&style=for-the-badge)](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}, |
|
} |
|
``` |