Unlocking the maximum potential of major language models (LLMs) for real-world applications demands a focused approach to fine-tuning. While these models demonstrate remarkable capabilities, directly deploying them often falls short of expectations due to shortcomings in handling noisy data and specific use cases. Robust deployment hinges on a mult