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AI EngineeringTeX

Axolotl

by Orchestra-Research

Axolotl is an AI Engineering skill for Claude Code, published by Orchestra-Research in AI-Research-SKILLs.

11.6K stars838 forkson Orchestra-Research/AI-Research-SKILLsAdded 2026/07/19+1% in starsRepository updated 2026/06/16
View source on GitHubDownload repo ZIP
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Install in seconds
Install Axolotl
Copy Axolotl into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/main/03-fine-tuning/axolotl ~/.claude/skills/axolotl

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/Orchestra-Research/AI-Research-SKILLs.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
03-fine-tuning/axolotl/SKILL.md in Orchestra-Research/AI-Research-SKILLs
Installs to
~/.claude/skills/axolotl
Collection
One of 50 skills cataloged from this repository
Category
AI Engineering — 3670 skills

What Axolotl does

Comprehensive guidance for fine-tuning LLMs using Axolotl, including YAML configuration, 100+ model support, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, and multimodal training.

Axolotl is cataloged under AI Engineering on DirSkills. Axolotl comes from a repository tagged ai, ai-research, claude, claude-code and claude-skills.

Documentation

README

Axolotl Skill

Comprehensive assistance with axolotl development, generated from official documentation.

When to Use This Skill

This skill should be triggered when:

  • Working with axolotl
  • Asking about axolotl features or APIs
  • Implementing axolotl solutions
  • Debugging axolotl code
  • Learning axolotl best practices

Quick Reference

Common Patterns

Pattern 1: To validate that acceptable data transfer speeds exist for your training job, running NCCL Tests can help pinpoint bottlenecks, for example:

./build/all_reduce_perf -b 8 -e 128M -f 2 -g 3

Pattern 2: Configure your model to use FSDP in the Axolotl yaml. For example:

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Axolotl

  • What else does Orchestra-Research publish alongside Axolotl?

    Axolotl is one of 50 skills that DirSkills catalogs from Orchestra-Research/AI-Research-SKILLs, the repository it ships in. Its siblings there include AWQ Quantization, Autoresearch and BigCode Evaluation Harness. Each one is a separate skill with its own page in this directory, installs the same way Axolotl does, and is maintained by Orchestra-Research in that same repository. The rest of the collection is listed on the Orchestra-Research/AI-Research-SKILLs page.

  • How does Axolotl compare to other AI Engineering skills?

    Axolotl ranks #329 by stars among the 3670 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Axolotl against them. Open each page to compare what they document and how they install.

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