The author is working through a book on building a large language model and sharing insights and struggles in a blog post series. The latest post covers implementing self-attention with trainable weights, a key aspect of transformer-based language models. The author dives into details of how attention mechanisms work, explaining concepts like projection matrices and dot products. The post provides a clear and detailed explanation, focusing on the mechanics rather than the theory behind the process. The author shares personal challenges in understanding the material and aims to help readers grasp complex concepts. The post offers valuable insights into the inner workings of language models.
https://www.gilesthomas.com/2025/03/llm-from-scratch-8-trainable-self-attention