<ul><li>In 2025, fine-tuning large language models like LLaMA for code completion has become more accessible with improved tools and techniques.</li><li>Key steps involve preparing the codebase, instruction tuning, retrieval-augmented fine-tuning, fine-tuning with PEFT/LoRA, training setup, and inference with retrieval augmentation.</li><li>Best practices in 2025 for fine-tuning LLMs like LLaMA emphasize hardware optimization, data preparation, training strategy, retrieval augmentation, security measures, and deployment strategies.</li><li>The future of AI-assisted coding lies in smarter, leaner, and more responsive models that integrate seamlessly into developer environments, offering personalized AI coding assistants for improved efficiency and security measures.</li></ul>

Fine-Tuning LLaMA for Code Completion (2025 Edition)

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