I Built GPT-2 from Scratch in PyTorch

📰 Medium · Deep Learning

Learn to build GPT-2 from scratch in PyTorch and understand its architecture, training loop, and inference in a single file

advanced Published 19 May 2026

Action Steps

Build the GPT-2 architecture using PyTorch modules
Implement the training loop with a custom dataset and optimizer
Configure the model for inference and generate text samples
Test the model's performance on a validation set
Apply the trained model to a specific NLP task, such as language translation or text summarization

Who Needs to Know This

This guide benefits NLP engineers, AI researchers, and software engineers who want to implement and customize GPT-2 models for their projects. It requires a strong foundation in PyTorch and deep learning concepts.

Key Insight

💡 Implementing GPT-2 from scratch in PyTorch requires a deep understanding of the model's architecture, training loop, and inference mechanisms.