---

name: cli-and-configs description: "Build and debug TRL CLI commands, YAML configs, dataset mixture configs, accelerate-launch argument patterns, env configs, and bundled TRL skills commands." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

TRL CLI and Configs

Use this sub-skill when a task is about invoking trl, constructing reproducible CLI/YAML configurations, translating Python trainer arguments into CLI flags, or debugging parser/config errors.

Use this for

• Choosing top-level commands: trl sft, trl dpo, trl grpo, trl reward, trl rloo, trl kto, trl env, trl skills, and trl vllm-serve.
• Building safe command lines or YAML files from model, dataset, training, and accelerate-launch arguments.
• Explaining --config YAML behavior, env: sections, CLI-overrides-config precedence, and dataset mixture syntax.
• Debugging unknown arguments, boolean flag spelling, required output_dir or model_name_or_path/model errors, and misplaced subcommand arguments.
• Using trl skills list/install/uninstall command syntax.

Route away

• Trainer objectives, loss semantics, reward modeling behavior, and algorithm-specific hyperparameter meaning belong in ../core-training/SKILL.md.
• Distributed strategy meaning, vLLM server architecture, DeepSpeed/FSDP tradeoffs, and backend troubleshooting belong in ../scaling-and-backends/SKILL.md.
• Dataset column schemas, reward function contracts, chat template formatting, and data preprocessing semantics belong in ../data-and-rewards/SKILL.md.

Fast workflow

1. Identify the command family and whether the user wants a shell command, a YAML file, or both.
2. Put trl <subcommand> first; training subcommands accept script/trainer/model/dataset fields and also pass remaining accelerate-launch flags through accelerate launch.
3. Prefer YAML for reproducibility when there are more than a few flags, environment variables, or dataset mixtures.
4. Use CLI flags after --config path.yaml only for intentional overrides; command-line values win over YAML defaults.
5. For safe template generation, run python scripts/build_trl_command.py --help from this sub-skill directory, or copy the helper into a scratch location and render templates without launching training.

References

• references/cli-reference.md covers commands, parser behavior, common flags, trl env, trl skills, and trl vllm-serve.
• references/configuration.md covers YAML config files, dataset mixtures, environment variables, accelerate config patterns, and conversion from Python recipes.
• references/troubleshooting.md covers parser errors, bool spelling, config precedence, dataset conflict handling, and command-specific warnings.
• scripts/build_trl_command.py renders shell/YAML templates for sft, dpo, grpo, reward, rloo, and kto; it does not import TRL or start training.