unsloth
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
npx skills add OpenRaiser/NanoResearch --skill unsloth --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 ### references/ Organized documentation extracted from official sources. These files contain: - Detailed explanations - Code examples with language annotations - Links to original documenta
- When to Use This Skill
- Quick Reference
- Common Patterns
- Reference Files
- Working with This Skill
- For Beginners
- For Specific Features
- For Code Examples
- Resources
- references/
- scripts/
- assets/
- Notes
- Updating
What does the unsloth skill do?
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
How do I install it?
Run `npx skills add OpenRaiser/NanoResearch --skill unsloth --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From OpenRaiser/NanoResearch, a repository with 1,480 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
