Unsloth, a method designed to enhance the efficiency of Language Learning Models (LLMs), aims to combat inefficiencies and redundancies present in large models, leading to faster processing speeds and reduced computational costs. By integrating Unsloth with SDPA (Scaled Dot-Product Attention) in MonsterAPI's solution, users can experience significant performance boosts and improved context lengths for larger LLMs. This integration enables faster response times, reduces latency, improves overall efficiency, enhances the ability to handle larger datasets and more complex queries, and provides better handling of long-range dependencies. With Unsloth and SDPA, MonsterAPI delivers a powerful toolkit for building and deploying custom and efficient Large language models, paving the way for more accessible, sustainable, and innovative AI technologies.