L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

cli-and-operations

cli-and-operations

Guides agents using Axolotl CLI commands, launcher flags, agent-docs, config-schema, install checks, merge LoRA, inference, vLLM serving, evaluation, fetch, and quantize operations.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: cli-and-operations description: "Guides agents using Axolotl CLI commands, launcher flags, agent-docs, config-schema, install checks, merge LoRA, inference, vLLM serving, evaluation, fetch, and quantize operations." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

CLI and Operations

Use this sub-skill when the task is about an axolotl command, CLI flags, command construction, agent-docs, config-schema, install checks, fetching examples, preprocessing runs, training launchers, inference, evaluation, LoRA merge, sharded FSDP merge, vLLM serving, cloud invocation, or post-training quantization.

Read First

  • references/cli-reference.md for the command map, launcher argument placement, option syntax, and agent-docs/config-schema usage.
  • references/operations.md for safe operational sequences from install checks through preprocess, train, evaluate, inference, merge, vLLM serve, fetch, and quantize.
  • references/troubleshooting.md for symptom-driven fixes around missing entry points, broken imports, config paths, overrides, launcher args, chat/Gradio conflicts, adapter paths, vLLM, and cloud configs.
  • scripts/axolotl_command_builder.py to build a safely quoted Axolotl command from a config path, command name, launcher, and JSON options without executing it.
  • scripts/check_axolotl_install.py to check package metadata, top-level import, axolotl on PATH, and axolotl --help without starting training or loading a model.

Fast Workflow

  1. Check the local install first when the task mentions command not found, import errors, or a failing help/schema command.
  2. Use axolotl agent-docs --list, axolotl agent-docs <topic>, and axolotl config-schema --field <name> for installed-package truth before guessing config keys.
  3. Build commands with config path first, Axolotl overrides before the -- separator, and launcher-specific args after --.
  4. Prefer axolotl preprocess config.yml --debug before long training when dataset formatting, chat_template, labels, packing, or tokenization is uncertain.
  5. Route field-level YAML, dataset, method, model, adapter, DeepSpeed, FSDP, or performance tuning questions to the matching sibling sub-skill after the command route is clear.

Boundaries

This sub-skill owns Axolotl CLI entry points, safe command construction, install/entry-point checks, operational sequencing, fetch, agent-docs, config-schema, cloud flags, inference/evaluation/merge/vLLM/quantize command routes, and common CLI failures. Route detailed config fields and dataset shapes to data-and-configs, method recipes to SFT/pretraining or RL/preference sub-skills, model/adapters to model-loading-and-adapters, and distributed/performance backend tuning to distributed-and-performance.

Skills enregistrées