Full supervised fine-tuning is appropriate when:
- You have ample compute resources
- You need maximum performance on a specific task
- Your task differs substantially from pre-training
- You plan to deploy this single model
If you're experimenting, trying multiple approaches, or have limited compute, start with LoRA instead. Full SFT is the heavy hammer.