Unsloth
FreeAccelerate LoRA/QLoRA fine-tuning with less VRAM.
Free · Opens the source repo
What Unsloth does
Unsloth is a skill designed to assist developers and data scientists in fine-tuning models using LoRA and QLoRA techniques. It aims to enhance the efficiency of model training by providing guidance and resources that can lead to a 2-5x increase in fine-tuning speed while reducing the VRAM requirements. This skill is particularly valuable for those who work with large language models and need to optimize their training processes without compromising on performance.
The skill includes comprehensive documentation and resources that cover various aspects of working with unsloth. Users can find detailed explanations, code examples, and links to original documentation within the bundled reference files. These resources are structured to facilitate quick navigation, making it easier for users to locate the information they need, whether they are beginners or experienced practitioners.
For newcomers, the skill offers a starting point with getting started guides and tutorials that introduce foundational concepts. More experienced users can dive into specific features and common patterns through the quick reference section, which extracts key usage examples from the official documentation. This dual approach ensures that users at all levels can benefit from the skill's offerings.
Overall, Unsloth serves as a practical tool for anyone looking to streamline their model fine-tuning workflow and maximize the efficiency of their computational resources. Its focus on providing structured, accessible documentation makes it a useful addition for developers and data scientists alike.
When to use it
Use this skill when you are implementing unsloth solutions, debugging related code, or seeking best practices for LoRA/QLoRA fine-tuning.
When not to use it
This skill may not be suitable for users who are not working with LoRA or QLoRA techniques or those seeking features outside of fine-tuning assistance.
What you can build with it
Fine-Tuning Large Language Models
Use Unsloth to quickly fine-tune large language models with reduced VRAM requirements, enhancing your workflow.
Debugging LoRA Code
When encountering issues with LoRA implementations, leverage Unsloth for guidance and troubleshooting tips.
Learning Best Practices
Utilize Unsloth to access best practices and common patterns in LoRA/QLoRA fine-tuning to improve your model training strategies.
How to install Unsloth
View source1. Install with the skills CLI
npx skills add nousresearch/hermes-agent/unsloth --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by nousresearchUnsloth Skill
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 full 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 documentation
- Table of contents for quick navigation
scripts/
Add helper scripts here for common automation tasks.
assets/
Add templates, boilerplate, or example projects here.
Notes
- This skill was automatically generated from official documentation
- Reference files preserve the structure and examples from source docs
- Code examples include language detection for better syntax highlighting
- Quick reference patterns are extracted from common usage examples in the docs
Updating
To refresh this skill with updated documentation:
- Re-run the scraper with the same configuration
- The skill will be rebuilt with the latest information
Frequently asked questions about Unsloth
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