update readme

README.md

@@ -7,73 +7,50 @@ tags:
 - 'arabic '
 - text-generation
 ---
-# Model Description
-
-ArabianGPT is a custom-trained version of the GPT-2 base model, specifically tailored for the Arabic language. It is designed to understand and generate Arabic text, making it suitable for various natural language processing tasks in Arabic.
-
-
-| Specification         | Value    |
-|-----------------------|----------|
-| Model Name            | ArabianGPT|
-| Architecture          |GPT-2     |
-| Layers                | 12       |
-| MAL (Model Attention Layers) | 12 |
-| Model Size            | 134M     |
-| Context Window Size   | 768      |
-
-
-# Training
-* Dataset: Abu Elkhiar Corpus
-* Size: 15.5 GB
-* Number of Words: 237,814,541
-* Number of Tokens: 1,752,421,071
-
-
-# Compute
-
-| Model            | Hardware      | Num of Examples (seq len = 768) | Batch Size | Num of Steps | Time (in days) | Loss
-|------------------|---------------|---------------------------------|------------|--------------|----------------|----------------|
-| ArabianGPT-base  | NDIVIA A100   | 7.5M                            | 512       | 313.5K       | 3              | 3.97           |
-
-
-> The model was trained on the Abu Elkhiar dataset, a comprehensive Arabic text corpus encompassing a wide range of topics. The training process focused on adapting the model to understand the nuances and complexities of the Arabic language.
-
-# Tokenizer
-Type: Custom trained SentencePiece tokenizer
-Vocabulary Size: 64K
-
-> We employed AraNizer, a custom trained tokenizer based on the SentencePiece model, with a vocabulary size of 64K. This choice was made to optimize the model's performance for the specific characteristics of the Arabic language.
-
-More info about AraNizer can be found here [Link](https://github.com/omarnj-lab/aranizer/tree/main)
-
-
-# Usage
-ArabianGPT can be used for text generation tasks in Arabic.
-
-### How to use
-
-Here is how to use this model to generate ruby function documentation using Transformers SummarizationPipeline:
-
+# ArabianGPT Model Overview
+
+## Introduction
+ArabianGPT is a GPT-2 based model, custom-trained for the Arabic language, as part of the ArabianLLM initiatives at Prince Sultan University's Robotics and Internet of Things Lab.
+
+## Key Features
+- **Architecture**: GPT-2
+- **Model Size**: 134 million parameters
+- **Layers**: 12
+- **Model Attention Layers (MAL)**: 12
+- **Context Window Size**: 768 tokens
+
+## Training
+- **Dataset**: Abu Elkhiar Corpus
+- **Data Size**: 15.5 GB
+- **Words**: 237.8 million
+- **Tokens**: Over 1.75 billion
+- **Hardware**: NDIVIA A100
+- **Training Scale**: 7.5 million examples
+- **Training Duration**: 3 days
+- **Performance**: Final loss of 3.97
+
+## Role in ArabianLLM Initiatives
+ArabianGPT 0.1B 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 SummarizationPipeline:
 ```python
 from transformers import pipeline
 
-pipe = pipeline("text-generation", model="riotu-lab/ArabianGPT-base" , max_new_tokens = 512)
-
+pipe = pipeline("text-generation", model="riotu-lab/ArabianGPT-base", max_new_tokens=512)
 text = ''
-
 pipe.predict(text)
 ```
 
-# Limitations
+## Limitations and Ethical Considerations
 
-> As with any language model, ArabianGPT may have limitations in understanding context or generating text in certain scenarios. Users should be aware of these limitations and use the model accordingly.
+- The model may have context understanding or text generation limitations in certain scenarios.
+- Emphasis on ethical use to prevent misinformation or harmful content propagation.
 
-# Ethical Considerations
-We emphasize responsible usage of ArabianGPT. Users should ensure that the generated text is used ethically and does not propagate misinformation or harmful content.
+## Acknowledgments
 
+Special thanks to Prince Sultan University, particularly the Robotics and Internet of Things Lab.
 
-# Acknowledgments
-> We thank Prince Sultan University, especially the Robotics and Internet of Things Lab, for their support.
+## Contact Information
 
-# Contact
-For inquiries regarding ArabianGPT, please contact riotu@psu.edu.sa.
+For inquiries: [riotu@psu.edu.sa](mailto:riotu@psu.edu.sa).