This final chapter beautifully ties everything together. Instruction fine-tuning is such a crucial step to unlock the real potential of LLMs, making them genuinely useful and adaptable for practical tasks. I appreciate how the chapter balances technical depth with hands-on guidance especially the focus on dataset curation and evaluation, which are often overlooked. Excited to try out the techniques like LoRA and custom masking in my own projects. Thanks for sharing this comprehensive journey!