# 🚀 Misraj Unstructured Data Dump (MUDD)

*A large-scale Arabic text dataset translated from SlimPajama-627B for pretraining Arabic language models*

## 📚 Dataset Summary

MUDD is a substantial dataset comprising *4,758,338 rows* of unstructured, plain Arabic text. Each entry includes Arabic text and retains its UUID from the original source. This dataset provides high-quality Arabic content specifically designed for pretraining large language models (LLMs) and advancing Arabic natural language processing (NLP) research.

## 🌟 Key Features

* 📏 **Size**: 4,758,338 rows of Arabic text
* 🗣️ **Language**: Arabic (translated from English)
* 📌 **Source**: Selected subset of [SlimPajama-627B](https://huggingface.co/datasets/cerebras/SlimPajama-627B)
* 🤖 **Translation Model**: [Mutarjim](https://arxiv.org/abs/2505.17894)
* 📝 **Format**: Plain text with UUID identifiers

## 🗃️ Dataset Details

### 🌐 Source Data

The foundation of MUDD is [SlimPajama-627B](https://huggingface.co/datasets/cerebras/SlimPajama-627B), a high-quality English text dataset containing:

* 📈 627 billion tokens
* ♻️ Deduplicated content
* 🌍 Diverse sources including web pages, Wikipedia, GitHub, and books

*Note*: MUDD is derived from a carefully selected subset of SlimPajama-627B, not the complete dataset.

### 🔄 Translation Process

The Arabic content was generated using *Mutarjim*, a high-performance Arabic-English translation model built on the [Kuwain-1.5B](https://arxiv.org/abs/2504.15120) architecture. The translation involved:

1. 🛠️ *Pre-training*: On extensive monolingual Arabic and English corpora
2. 🎯 *Fine-tuning*: Using high-quality, human-curated parallel sentence pairs for accurate Arabic translations

## 📂 Dataset Structure

```json
{
    "uuid": {
        "dtype": "string",
        "_type": "Value"
    },
    "plain_text": {
        "dtype": "string",
        "_type": "Value"
    }
}
```

## 💡 Usage

### 📥 Loading the Dataset

```python
from datasets import load_dataset

dataset = load_dataset("Misraj/mudd")
```

### 📋 Example Usage

```python
# Access the first example
example = dataset['train'][0]
print(f"UUID: {example['uuid']}")
print(f"Arabic Text: {example['plain_text']}")
```

## 🎯 Intended Use Cases

* 🤗 **Pretraining Arabic LLMs**: Large-scale, high-quality Arabic text corpus for training new language models
* 🔍 **Arabic NLP Research**: Supporting research initiatives focused on Arabic language processing
* 🚦 **Downstream Applications**: Reliable source for projects requiring extensive and diverse Arabic text data

## 📊 Dataset Statistics

| 📏 Metric         | 📌 Value                 |
| ----------------- | ------------------------ |
| Total Rows        | 4,758,338                |
| Language          | Arabic                   |
| Source            | SlimPajama-627B (subset) |
| Translation Model | Mutarjim                 |
| Format            | Plain text               |

## 📖 Citations

If you use this dataset, please cite:

```bibtex
@misc{misraj2025mudd, 
  title        = {Misraj Unstructured Data Dump (MUDD)},
  author       = {Khalil Hennara, Muhammad Hreden, Mohamed Motaism Hamed, Zeina Aldallal, Sara Chrouf, Safwan AlModhayan, Ahmed Bustati},
  year         = {2025},
  publisher    = {MisrajAI},
  howpublished = {\url{[https://huggingface.co/datasets/Misraj/mudd](https://huggingface.co/datasets/Misraj/mudd)}}
}
```