SakanaAI/self-adaptive-llms is an adaptive framework called Transformer², designed to address the challenges of traditional fine-tuning methods, which are computationally intensive and have static capabilities in handling diverse tasks. This framework adjusts large language models (LLMs) in real time during inference using a two-step mechanism: first, a scheduling system identifies task attributes; then, task-specific 'expert' vectors trained via reinforcement learning are dynamically mixed to achieve target behavior for the input prompt. Key advantages include real-time task adaptability, computational efficiency, and flexibility. Developed by the SakanaAI team, this project is open-source on GitHub, currently boasting 195 stars and 12 forks.