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Natural language processing (NLP) has evolved significantly over the years, from simple text analysis to advanced models like ChatGPT. This section explores the journey of NLP through key milestones such as Turing Tests, Transformer architectures, and GPT advancements. The Role of Language in Intelligence Language is a unique characteristic tha ...

From Pre-training to Post-training Large language models are usually built in two major stages: Pre-training: The model learns to predict the next token given a prefix, acquiring broad linguistic competence. Post-training: After the model can "speak", we teach it to "think". This stage splits into Supervised Fine-Tuning (S ...

Reinforcement Learning from Human Feeedback (RLHF) aligns language models with human preferences through a multi-stage process. Modern large language model pipelines commonly incorporate RLHF, often combining techniques like Direct Preference Optimization (DPO) followed by Proximal Policy Optimization (PPO). This guide focuses on implementing t ...