Modern large language model training involves a pipeline including pretraining, supervised fine-tuning, LoRA/QLoRA for efficient adaptation, RLHF for aligning with human preferences, and GRPO for enhanced reasoning. This process is crucial as it ensures models are not only knowledgeable but also behave appropriately in real-world applications, benefiting developers through improved model efficiency and usability.
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