README.md

---
license: apache-2.0
language:
- ar
pipeline_tag: text-generation
tags:
- 'arabic '
- text-generation
widget:
- text: "أعلنت وزارة الحج في المملكة العربية السعودية"
  example_title: "مثال ١"
- text: "يبدو اليوم جميلا، سأقوم بتحضير"
  example_title: "مثال ٢"
- text: "إن التقنيات الحديثة"
  example_title: "مثال ٣"
---
# ArabianGPT Model Overview

## Disclaimer for the Use of Large Language Models (LLMs) for Text Generation

<p style="color: red;">We disclaim all responsibility for any harm, inaccuracies, or inappropriate content generated by ArabianGPT-0.1B, and users engage with and apply the model's outputs at their own risk.</p>

> **Important Note:** Currently, we offer a raw pre-trained model. Our team is actively working on releasing instruction-based LLMs that are fine-tuned and augmented with LRHF. The first set of pre-trained models has been made available for community exploration. While we do have models fine-tuned for specific tasks such as summarization and sentiment analysis, they are still in the development phase.


## How you can use this Pre-Trained?
You are invited to utilize this pre-trained, native Arabic language model as an experimental tool to assess its capabilities, aid in its fine-tuning, and evaluate its performance across a variety of downstream tasks. We encourage you to review our technical report for a comprehensive understanding of the model's performance metrics and the specific downstream tasks it has been tested on. This will provide valuable insights into its applicability and effectiveness in diverse applications.


## Introduction
ArabianGPT-0.1B, developed under the ArabianLLM initiatives, is a specialized GPT-2 model optimized for Arabic language modeling. 
It's a product of the collaborative efforts at Prince Sultan University's Robotics and Internet of Things Lab, focusing on enhancing natural language modeling and generation in Arabic. 
This model represents a significant stride in LLM research, specifically addressing the linguistic complexities and nuances of the Arabic language.

## Key Features
- **Architecture**: GPT-2
- **Model Size**: 134 million parameters
- **Layers**: 12
- **Model Attention Layers (MAL)**: 12
- **Context Window Size**: 768 tokens

## Training
- **Dataset**: Scraped Arabic newspaper articles
- **Data Size**: 15.5 GB
- **Words**: 237.8 million
- **Tokenizer**: Aranizer 64K
- **Tokens**: Over 1.75 billion
- **Hardware**: 2 NDIVIA A100 GPUs 
- **Training Scale**: 7.5 million examples
- **Training Duration**: 3 days
- **Performance**: Final loss of 3.97


## Role in ArabianLLM Initiatives
ArabianGPT-0.1B (Base Model) is crucial for advancing Arabic language processing, addressing challenges unique to Arabic morphology and dialects.

## Usage
Suitable for Arabic text generation tasks. Example usage with Transformers Pipeline:
```python
from transformers import pipeline

pipe = pipeline("text-generation", model="riotu-lab/ArabianGPT-01B", max_new_tokens=512)
text = ''
pipe.predict(text)
```

## Limitations and Ethical Considerations

- The model may have context understanding or text generation limitations in certain scenarios.
- Emphasis on ethical use to prevent misinformation or harmful content propagation.

## Acknowledgments

Special thanks to Prince Sultan University, particularly the Robotics and Internet of Things Lab.

## Contact Information

For inquiries: [riotu@psu.edu.sa](mailto:riotu@psu.edu.sa).

## Disclaimer for the Use of Large Language Models (LLMs) for Text Generation

<p style="color: red;">We disclaim all responsibility for any harm, inaccuracies, or inappropriate content generated by ArabianGPT-0.1B, and users engage with and apply the model's outputs at their own risk.</p>