Phase 13 · Fine-Tuning & Adapting LLMs
TopicsFull Fine-Tuning vs PEFT
Part of the AI Engineer Roadmap.
Summary
Full fine-tuning updates every model weight (expensive, needs lots of GPU memory); Parameter-Efficient Fine-Tuning updates a small subset — PEFT is the practical default outside large labs.
How to Learn This
- 1Compare the GPU memory and cost requirements of full fine-tuning vs. PEFT for a given model size.
- 2Learn why PEFT can match full fine-tuning quality on most task-specific use cases.
- 3Identify which approach makes sense for your hardware budget before starting a project.
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