LoRA vs Full Fine-Tune: When Each One Wins
Cost, quality, time-to-train, deployment story. Real numbers from training Gemma 3 1B both ways.
LoRA, QLoRA, full SFT. When fine-tuning beats prompting and when it doesn't.
5 working guides in this section.
Cost, quality, time-to-train, deployment story. Real numbers from training Gemma 3 1B both ways.
Same training run on each platform. Per-hour, per-job, hidden fees, reliability scoring.
Dataset prep, Unsloth config, LoRA targets, eval loop, and pushing to HuggingFace. Working notebook you can clone.
Memory math, throughput tradeoff, quality delta. Picking based on your actual GPU.
12 things to check before you waste $200 on a bad training run. Format, dedup, contamination, eval split.