Implementing GPT-2 From Scratch (Transformer Walkthrough Part 2/2)

In this monologue podcast, Neel walks through the process of implementing GPT-2 from scratch, explaining the conceptual underpinnings of transformers and their various components like attention and lanorm. He emphasizes the importance of understanding the internal computations of language models for mechanistic interpretability research, and encourages listeners to code along using a template notebook with tests. Neel also touches on the practical aspects of coding, including debugging, testing, and visualizing attention patterns, and briefly demonstrates how to train a model and generate text, though the training demo is cut short due to technical issues.