Repeng enables rapid training (under 60 seconds) of control vectors that steer language model outputs in desired directions. It wraps transformer models with a ControlModel interface and trains ControlVector objects by contrasting paired positive/negative examples (e.g., high vs. sober personas). The trained vectors can then be applied at varying strengths during generation to influence model behavior without fine-tuning.