Fundamentals · Part 13How LLMs Work
From Base Model to Assistant: SFT, RLHF and DPO
How a next-token predictor becomes a helpful assistant: supervised fine-tuning, reward models, RLHF with PPO, and DPO, worked with real numbers.
4 articles.
Fundamentals · Part 13How LLMs Work
How a next-token predictor becomes a helpful assistant: supervised fine-tuning, reward models, RLHF with PPO, and DPO, worked with real numbers.
Fundamentals · Part 16How LLMs Work
How researchers read an LLM's internals: the logit lens, superposition, sparse autoencoders, circuits and steering, with real numbers and honest limits.
Math · Part 16Math for LLMs
The equations behind RLHF and reasoning RL: the log-derivative trick, baselines, PPO's clip, Bradley-Terry, the KL-regularized optimum, DPO and GRPO.
Interpretability · Part 11Interpretability
What looking inside a model can and can't check about its honesty: lie and sycophancy probes, model diffing and real audits, measured on Gemma 2 2B.