Introduction: Fine-tuning transforms general-purpose language models into specialized tools for your domain. While prompting works for many tasks, fine-tuning delivers consistent behavior, lower latency, and reduced token costs when you need the model to reliably follow specific formats, use domain terminology, or exhibit particular reasoning patterns. This guide covers practical fine-tuning strategies: preparing high-quality training […]
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