My Projects with research papers implementations, and the documentation for each.
nanograd is a neural net engine (command line interface and python library) inspired by micrograd and tinygrad, built upon a PyTorch-like API. It aims to provide users with easy-to-use tools for creating and utilizing various neural network architectures.
Welcome to Axon: AI Research Lab! This repository serves as a collaborative platform for implementing cutting-edge AI research papers and conducting novel research in various areas of artificial intelligence. Our mission is to bridge the gap between theoretical research and practical applications by providing high-quality, reproducible implementations of seminal and contemporary AI papers: InstructGPT, llama, transformers, diffusion models, RLHF, etc...
X-Llama is an advanced language model framework, inspired by the original Llama model but enhanced with additional features such as Grouped Query Attention (GQA), Multi-Head Attention (MHA), and more. This project aims to provide a flexible and extensible platform for experimenting with various attention mechanisms and building state-of-the-art natural language processing models
LlTRA stands for: Language to Language Transformer model from the paper "Attention is all you Need", building transformer model:Transformer model from scratch and using it for translation using pytorch, Develop a specialized language-to-language transformer model that accurately translates from the Arabic language to the English language, ensuring semantic fidelity, contextual awareness, cross-lingual adaptability, and the retention of grammar and style. The model should provide efficient training and inference processes to make it practical and accessible for a wide range of applications, ultimately contributing to the advancement of Arabic-to-English language translation capabilities.
I developed a Python library for transformers, leveraging the architecture I previously designed. With this library, users can freely install and utilize the transformer architecture.
Neural Network From Scratch using Java and processing environment. Brain is a neural network simulator tool implemented in Java using the Processing environment. The project aims to provide a visual representation of the decision-making process of a neural network controlling the movements of a snake. The tool incorporates a genetic algorithm to optimize the neural network's performance. Through real-time visualization, users can gain insights into the neural network's behavior, identify patterns, and witness the improvement achieved through the genetic algorithm.