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The scripts are in the repository, not in the installed package. Clone it, then cd recipes/community before running the commands below. Browse this recipe on GitHub.
Recipes contributed by people trying the SDK on their own problems, published so the next person starts from someone’s real run instead of from zero. Each directory carries the script that was actually run, the numbers it produced with intervals, and an honest account of what did not work. These are not maintained by While. Read the README in each one for the version it was run against and what the author would do differently.

can-the-judge-be-trusted

Grade the same rollouts two ways — with rubric_judge() and with a deterministic verifier — and measure where the LLM judge disagrees with the rule.

force-the-branch

Seat: a post-training engineer at a startup that ships one production agent, trying to find out whether a small open model can take over the boring half of it.

hosted-grpo-vs-sft

Seat: an open-model fine-tuner who lives in TRL and Hugging Face, here for clean exports, a LoRA run, a hosted result and a cost line.

how-much-contamination-survives

Measure what fraction of real held-out contamination wai.decontaminate() actually removes, using human-labelled paraphrase pairs as ground truth instead of a planted copy.

same-entrypoint-before-after

Seat: a post-training engineer at a startup that ships one production agent, trying to find out whether a small open model can take over the boring half of it.

the-step-the-course-skips

The eight-lesson course for people who have never trained a model stops one line short of the training: # 2.

what-trl-does-with-the-loss-mask

wai.export(…, format=“trl”) writes a loss_mask on every row and reports mask_mode: “assistant”.

who-protects-the-holdout

decontaminate() applies four rules in order.
Last modified on September 20, 2026