If you're fine-tuning LLMs and tired of waiting hours or running out of memory, this skill gives you expert guidance on Unsloth's optimization techniques. It covers LoRA and QLoRA implementations with 2-5x faster training speeds and 50-80% memory reduction across popular models like Llama, Mistral, Gemma, and Qwen. The documentation here is pulled from official sources, so you get the real patterns and examples without hunting through GitHub repos. Good for both getting started quickly and debugging when your training runs go sideways. Honestly, if you're doing any serious fine-tuning work, knowing these optimization tricks will save you real time and compute costs.

skills.sh installs
1K
GitHub stars
14.4K
last updated
Aug 21, 2026

Install

$ npx -y skills add orchestra-research/ai-research-skills --skill unsloth --agent claude-code

Installs into .claude/skills of the current project.

Files

Unsloth Skill

Comprehensive assistance with unsloth development, generated from official documentation.

When to Use This Skill

This skill should be triggered when:

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

Quick Reference

Common Patterns

Quick reference patterns will be added as you use the skill.

Reference Files

This skill includes comprehensive documentation in references/:

  • llms-txt.md - Llms-Txt documentation

Use view to read specific reference files when detailed information is needed.

Working with This Skill

For Beginners

Start with the getting_started or tutorials reference files for foundational concepts.

For Specific Features

Use the appropriate category reference file (api, guides, etc.) for detailed information.

For Code Examples

The quick reference section above contains common patterns extracted from the official docs.

Resources

Sponsors

Details

Repository
github.com/orchestra-research/ai-research-skills
Categories
AI & Agent Building, Data Science & ML
First seen
Jun 3, 2026

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