Post-training

Once the base training is done, developers often take additional steps to improve the model’s performance. This can include fine-tuning (training the model on a smaller, more specific dataset to specialize it for certain tasks) and RLHF, short for Reinforcement Learning from Human Feedback, which helps align the model’s behavior with what people actually want or expect from it in real-world use.