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-0.3B, 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-0.3B, 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**: 345 million parameters
- **Layers**: 24
- **Model Attention Layers (MAL)**: 16
- **Context Window Size**: 1024 tokens

## Training
- **Dataset**: Scraped texts contains scientific articles, and general texts
- **Data Size**: 23 GB
- **Tokenizer**: Aranizer 64K
- **Tokens**: Over 3.3 billion
- **Hardware**: 4 NDIVIA A100 GPUs 
- **Training Duration**: 45 days
- **Performance**:  loss of 3.82


## Role in ArabianLLM Initiatives
ArabianGPT-0.3B  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-03B", 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-0.3B, and users engage with and apply the model's outputs at their own risk.</p>