Ever wondered how to build your own ChatGPT model? Here's a practical approach: leverage PyTorch for the deep learning framework and Jupyter for interactive development. You can construct a large language model from scratch by working through transformer architecture, attention mechanisms, and training pipelines. PyTorch provides the essential tools for implementing neural networks efficiently, while Jupyter notebooks make the iterative process seamless—perfect for experimenting with model layers, loss functions, and optimization techniques. This hands-on approach demystifies how modern AI models work under the hood, giving you full control over architecture design and training parameters. Whether you're exploring LLM mechanics or building custom AI applications, this framework combination offers both flexibility and accessibility for developers at any level.