Inside LLMs: Understanding Transformer Architecture – A Guide for Marketers
The previous articles introduced pre-training and embeddings, positional information and attention. Now we can put those pieces together. What actually happens between token representations entering a language model and the model producing scores for the next token? The answer matters because transformer architecture attracts unusually convenient marketing myths. Attention becomes “make these words bold”. Learned … Read more