An Introduction to Language Modeling with GPT-2

The article by Jan Świątek delves into classical language modeling, explaining its core concepts and historical evolution from n-grams to transformer models like the GPT-2. It covers the basics of language modeling, how GPT-2 leverages the transformer architecture for text prediction, and details the steps involved in tokenization, model inference, and generating text sequences. The author also touches on the importance of understanding logits and the influence of temperature in adjusting the model's creativity. Essential libraries like Axon, Bumblebee, and Nx are discussed for working with GPT-2 in Elixir.