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In the context of the "The Complete Generative AI & LLMs Course 2026: From Zero to Expert!", which architectural component of a transformer model is primarily responsible for capturing long-range dependencies and contextual relationships within input sequences?

Considering the advanced topics in "The Complete Generative AI & LLMs Course 2026: From Zero to Expert!", what is the primary challenge associated with fine-tuning large language models (LLMs) for highly specialized downstream tasks, and how might parameter-efficient fine-tuning (PEFT) methods address it?

In the "The Complete Generative AI & LLMs Course 2026: From Zero to Expert!", when discussing the evaluation of generative models, what metric is most appropriate for assessing the diversity and novelty of generated text, going beyond simple accuracy or perplexity?