Update README.md

README.md

@@ -7,53 +7,68 @@ tags:
 - 'arabic '
 - text-generation
 ---
-Model Description
-Model Name: ArabicGPT-S
+# Model Description
+
+Model Name: ArabianGPT
 Architecture: GPT-2
 Layers: 12
 Model Size: 134M
 Context Window Size: 768
-
 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.
 
-Training
+# Training
 Dataset: Abu Elkhiar Corpus
 Size: 15.5 GB
 Number of Words: 237,814,541
 Number of Tokens: 1,752,421,071
+Number of Parameters : 134 M Params
 Epochs: 5.87
 Loss: 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 
+# 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.
 
-We employed AraNizer, a custom trained tokenizer based on the SentencePiece model, with a vocabulary size of 64. This choice was made to optimize the model's performance for the specific characteristics of the Arabic language.
+### How to use
 
-Usage
-ArabianGPT can be used for text generation
+Here is how to use this model to generate ruby function documentation using Transformers SummarizationPipeline:
 
-Limitations
-As with any language model, ArabicGPT may have limitations in understanding context or generating text in certain scenarios. Users should be aware of these limitations and use the model accordingly.
+```python
+from transformers import pipeline
 
-Ethical Considerations
+pipe = pipeline("text-generation", model="riotu-lab/Ghazal" , max_new_tokens = 512)
+
+text = ''
+
+pipe.predict(text)
+```
+
+# Limitations
+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.
+
+# 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.
 
-Citation
+# Citation
 If you use ArabianGPT in your research or application, please cite it as follows:
 
 @misc{ArabianGPT, 2023,
-title={ArabianGPT:  A GPT-2 Based Language Model for Arabic},
-author={Najar, Omar and Sibaee, Serry and Ghouti, Lahouari and Koubaa, Anis},
-affiliation={Prince Sultan University, Riyadh, Saudi Arabia},
-year={2023},
+  title={ArabianGPT: A GPT-2 Based Language Model for Arabic},
+  author={Najar, Omar and Sibaee, Serry and Ghouti, Lahouari and Koubaa, Anis},
+  affiliation={Prince Sultan University, Riyadh, Saudi Arabia},
+  year={2023},
 }
 
+# Acknowledgments
+We thank Prince Sultan University, especially the Robotics and Internet of Things Lab, for their support.
 
-Acknowledgments
-We thank Prince Sultan University espically Robotoics and Internet of Things Lab for suuport 
-
-Contact
-For inquiries regarding ArabicGPT-S, please contact onajar@psu.edu.sa
+# Contact
+For inquiries regarding ArabianGPT, please contact onajar@psu.edu.sa.