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The Art and Science of Fine-Tuning LLMs for Domain-Specific Excellence
Key advancements include in-context learning, which enables coherent text generation from prompts, and reinforcement learning from human feedback (RLHF), which fine-tunes models based on human responses. Techniques like prompt engineering have also enhanced LLM performance in tasks such as question answering and conversational interactions, marking a significant leap in natural language processing. Pre-trained language models…
