The Alignment Handbook provides robust, community-facing training recipes that cover the full post-training pipeline for language models. It includes recipes for supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and direct preference optimization (DPO), along with guidance on dataset selection, training hyperparameters, and evaluation metrics for measuring helpfulness and safety.