fine-tuning-customization
Fine-Tuning & Customization
Customize LLMs for specific domains using parameter-efficient fine-tuning and alignment techniques.
Unsloth 2026: 7x longer context RL, FP8 RL on consumer GPUs, rsLoRA support. TRL: OpenEnv integration, vLLM server mode, transformers 5.0.0+ compatible.
Decision Framework: Fine-Tune or Not?
| Approach | Try First | When It Works |
|---|---|---|
| Prompt Engineering | Always | Simple tasks, clear instructions |
| RAG | External knowledge needed | Knowledge-intensive tasks |
| Fine-Tuning | Last resort | Deep specialization, format control |
Fine-tune ONLY when:
- Prompt engineering tried and insufficient
- RAG doesn't capture domain nuances
- Specific output format consistently required
- Persona/style must be deeply embedded
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