Course Overview
In this course, we will examine the foundational techniques involved in fine-tuning large language models to achieve task-specific enhancements. By fine-tuning context of LLMs, we can achieve tailored improvements in accuracy, domain relevance, and robustness. In addition, this course introduces parameter-efficient fine-tuning (PEFT) techniques such as those implemented in Hugging Face's PEFT library and explore ways Intel's optimized hardware and software enhances GenAI fine-tuning workflows. (Duration: 19 minutes)
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Chapter Overview
In this course, we will examine the foundational techniques involved in fine-tuning large language models to achieve task-specific enhancements. By fine-tuning context of LLMs, we can achieve tailored improvements in accuracy, domain relevance, and robustness. In addition, this course introduces parameter-efficient fine-tuning (PEFT) techniques such as those implemented in Hugging Face's PEFT library and explore ways Intel's optimized hardware and software enhances GenAI fine-tuning workflows. (Duration: 19 minutes)Related Content
