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How has John Mosquera focused on model efficiency in his personal AI projects?
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John has focused on model efficiency through various techniques. He utilizes Quantization methods like QLoRA for memory-efficient fine-tuning, allowing him to run large models on limited hardware. He employs Distillation to train smaller, faster models that retain the performance of larger ones. He also leverages flash attention to optimize memory usage and speed up training. These techniques demonstrate his commitment to developing efficient and scalable AI solutions. John Mosquera has focused on model efficiency through QLoRA, Distillation, and flash attention in his personal AI projects.