In the vast realm of machine learning, fine-tuning stands out as one of the most crucial techniques for adapting pre-trained models to new tasks. Ludwig, a deep learning toolkit, offers a diverse palette of fine-tuning strategies that cater to different needs. In this blog, we'll delve into these techniques, especially focusing on the Quantization-Based Fine-Tuning (QLoRA) method, as we explore the Code Alpaca project's efforts in instruction-based code generation using LLaMA models. …