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mudd / README.md
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# πŸš€ Misraj Unstructured Data Dump (MUDD)
*A large-scale Arabic text dataset translated from SlimPajama-627B for pretraining Arabic language models*
## πŸ“š 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
* πŸ“ **Size**: 4,758,338 rows of Arabic text
* πŸ—£οΈ **Language**: Arabic (translated from English)
* πŸ“Œ **Source**: Selected subset of [SlimPajama-627B](https://huggingface.co/datasets/cerebras/SlimPajama-627B)
* πŸ€– **Translation Model**: [Mutarjim](https://arxiv.org/abs/2505.17894)
* πŸ“ **Format**: Plain text with UUID identifiers
## πŸ—ƒοΈ 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:
* πŸ“ˆ 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.
### πŸ”„ 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. πŸ› οΈ *Pre-training*: On extensive monolingual Arabic and English corpora
2. 🎯 *Fine-tuning*: Using high-quality, human-curated parallel sentence pairs for accurate Arabic translations
## πŸ“‚ Dataset Structure
```json
{
"uuid": {
"dtype": "string",
"_type": "Value"
},
"plain_text": {
"dtype": "string",
"_type": "Value"
}
}
```
## πŸ’‘ Usage
### πŸ“₯ Loading the Dataset
```python
from datasets import load_dataset
dataset = load_dataset("Misraj/mudd")
```
### πŸ“‹ 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
* πŸ€— **Pretraining Arabic LLMs**: Large-scale, high-quality Arabic text corpus for training new language models
* πŸ” **Arabic NLP Research**: Supporting research initiatives focused on Arabic language processing
* 🚦 **Downstream Applications**: Reliable source for projects requiring extensive and diverse Arabic text data
## πŸ“Š Dataset Statistics
| πŸ“ Metric | πŸ“Œ Value |
| ----------------- | ------------------------ |
| Total Rows | 4,758,338 |
| Language | Arabic |
| Source | SlimPajama-627B (subset) |
| Translation Model | Mutarjim |
| Format | Plain text |
## πŸ“– 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)}}
}
```