Description
In this workshop, participants will delve into the foundational concepts underlying large language models (LLMs). We will begin by exploring tokenisation, including word-based, character-based and subword-based approaches. Next, we will cover word embeddings, with a particular focus on word2vec. This will be followed by an in-depth look at self-attention and the transformer architecture. Attendees will then be divided into groups to experiment hands-on with different LLMs, applying their new knowledge and gaining practical experience.
