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- ## SET 1 - MAKEMORE (PART 2) 🔗
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-
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- [![Documentation](https://img.shields.io/badge/Documentation-Available-blue)](https://muzzammilshah.github.io/Road-to-GPT/Makemore-part2/)
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- ![Number of Commits](https://img.shields.io/github/commit-activity/m/MuzzammilShah/NeuralNetworks-LanguageModels-2?label=Commits)
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- [![Last Commit](https://img.shields.io/github/last-commit/MuzzammilShah/NeuralNetworks-LanguageModels-2.svg?style=flat)](https://github.com/MuzzammilShah/NeuralNetworks-LanguageModels-2/commits/main)
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- ![Project Status](https://img.shields.io/badge/Status-Done-success)
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-
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-  
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-
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- ### **Overview**
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- In this repository, a **Multi-Layer Perceptron (MLP)** language model inspired by the *Bengio et al. (2003)* research paper has been implemented for **character-level predictions**, following Andrej Karpathy's approach in the **Makemore - Part 2** video.
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-
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- The implementation demonstrates building and training the MLP model for sequence prediction while further enhancing the understanding of neural network architectures for language modeling.
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-
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-  
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-
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- ### **🗂️Repository Structure**
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-
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- ```plaintext
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- ├── .gitignore
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- ├── A-Main-Notebook.ipynb
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- ├── B-Main-Notebook.ipynb
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- ├── C-Main-Notebook.ipynb
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- ├── README.md
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- ├── notes/
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- │ ├── A-main-makemore-part2.md
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- │ ├── B-main-makemore-part2.md
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- │ ├── C-main-makemore-part2.md
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- │ └── README.md
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- └── names.txt
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- ```
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-
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- - **Notes Directory**: Contains detailed notes corresponding to each notebook section.
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- - **Jupyter Notebooks**: Step-by-step implementation and exploration of the MLP model.
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- - **README.md**: Overview and guide for this repository.
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- - **names.txt**: Supplementary data file used in training the model.
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-
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-  
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-
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- ### **📄Instructions**
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-
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- To get the best understanding:
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- 1. Start by reading the notes in the `notes/` directory. Each section corresponds to a notebook for step-by-step explanations.
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- 2. Open the corresponding Jupyter Notebook (e.g., `A-Main-Notebook.ipynb` for `A-main-makemore-part2.md`).
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- 3. Follow the code and comments for a deeper dive into the implementation details.
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-
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-  
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- ### **⭐Documentation**
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- For a better reading experience and detailed notes, visit my **[Road to GPT Documentation Site](https://muzzammilshah.github.io/Road-to-GPT/)**.
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- > **💡Pro Tip**: This site provides an interactive and visually rich explanation of the notes and code. It is highly recommended you view this project from there.
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-  
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- ### **✍🏻Acknowledgments**
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- Notes and implementations inspired by the **Makemore - Part 2** video by [Andrej Karpathy](https://karpathy.ai/).
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-
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  For more of my projects, visit my [Portfolio Site](https://muhammedshah.com).
 
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+ ---
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+ license: mit
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+ datasets:
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+ - MuzzammilShah/people-names
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+ language:
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+ - en
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+ model_name: Multi-Layer Perceptron (MLP) Language Model
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+ library_name: pytorch
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+ tags:
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+ - makemore
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+ - mlp
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+ - language-model
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+ - andrej-karpathy
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+ ---
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+
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+ # Multi-Layer Perceptron Language Model: Makemore (Part 2)
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+
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+ In this repository, a **Multi-Layer Perceptron (MLP)** language model inspired by the *Bengio et al. (2003)* research paper has been implemented for **character-level predictions**, following Andrej Karpathy's approach in the **Makemore - Part 2** video.
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+
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+ ## Overview
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+ The implementation demonstrates building and training the MLP model for sequence prediction while further enhancing the understanding of neural network architectures for language modeling.
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+
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+ ## Documentation
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+ For a better reading experience and detailed notes, visit my **[Road to GPT Documentation Site](https://muzzammilshah.github.io/Road-to-GPT/Makemore-part2/)**.
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+
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+ ## Acknowledgments
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+ Notes and implementations inspired by the **Makemore - Part 2** video by [Andrej Karpathy](https://karpathy.ai/).
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+
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  For more of my projects, visit my [Portfolio Site](https://muhammedshah.com).