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Method vs Recipe

posttrainllm should not confuse having a method on the roadmap with having a recipe that is likely to work.

Method

A method is a general capability or algorithm.

Examples:

Methods are necessary, but they are not enough. A method does not say when to use it, what data shape it needs, which failure it is meant to fix, or how to tell if it worked.

Recipe

A recipe is a task-specific application of a method.

A good recipe says:

Examples:

Weak method-level planStrong recipe-level plan
Try DPO.On qwen06-sql-expanded, run reference-anchored DPO on the 108 SQL hygiene pairs at lower LR than the failed SimPO run, then evaluate composed with the SFT adapter on the frozen 50-row synthetic execution gate and clean-SQL raw-output gate.
Try RLVR.Build 4-6 SQL candidates per prompt, score each by execution or gold equivalence, train/evaluate the model on selecting the best candidate before returning to open generation.
Try LoRA rank changes.On the same frozen SQL data, sweep rank {1,2,4,8} with fixed steps/LR/seed, report slice metrics, then inspect effective-update geometry before deciding whether more rank helped.
Add evals.Block reporting unless the run has baseline, candidate, slice metrics, trace review, performance, and a ship/retry/reject decision.

Why It Matters

The SQL hygiene run proves the difference. The method “preference tuning” was available and on-roadmap. The recipe used ref-free SimPO on 108 short pairs for 200 steps. That recipe collapsed generation:

synthetic execution: 0.860 -> 0.080
clean-SQL raw rate: 0.000 -> 0.000

The method was not disproved. The recipe failed.

Required Recipe Card

Before a new post-training run, write or update a card with this shape:

## <recipe name>

- Target:
- Method:
- Failure mode addressed:
- Data:
- Baseline:
- Candidate:
- Eval gate:
- Slice gates:
- Performance fields:
- Stop rule:
- Prior evidence:
- Result:

If the card cannot name the failure mode and eval gate, the run is not ready.