finetuning-method-selection
Decide whether to fine-tune at all, and route to the right method (SFT, DPO/ORPO/KTO, GRPO/RLVR, continued pretraining) and base model. Use when starting any fine-tuning effort, when unsure whether RAG or prompting would suffice, or when choosing between preference-optimization and reinforcement methods.
| Field | Value |
|---|---|
| Owner | wshobson |
| Curator | Thomas Cherickal |
| Source | wshobson/agents |
| Repo stars | 42,512 |
| License | MIT |
| Repo last push | 2026-11-09 |
Links
- Roles: llm-engineer
- Source repo: wshobson/agents
- Same repo: eval-harness-first, evaluation-methodology, dataset-curation, grpo-rlvr-training, lora-qlora-recipes, python-anti-patterns, python-background-jobs, python-code-style
- Registry seed skills for this role: llm-engineer seed skills