Modifications to a model after pre-training to change behavior or improve usefulness and safety (e.g., instruction tuning, preference optimization, safety tuning, or distillation). Post-training often changes model characteristics and can affect evaluation results, safety properties, and documentation baselines.
See: Fine-tuning; Pre-training