Unsloth Fine-Tuning Guide
Guides an agent through faster, lower-memory LoRA/QLoRA fine-tuning with Unsloth
- Repository
- Orchestra-Research/AI-Research-SKILLs
- Stars
- 14,195
- Licence
- MIT
- Files
- 3 files
What it does
Once installed, the agent can answer questions about Unsloth, a library for fine-tuning open AI language models. Fine-tuning means further training a model on your own examples so it behaves differently. This skill points the agent at bundled Unsloth documentation so it can suggest code and settings for faster training with less memory, using LoRA and QLoRA methods. The skill itself is documentation only; it does not train anything on its own.
Great for
- Developers who want to fine-tune Llama, Mistral, Gemma or Qwen models on a single GPU
- Engineers evaluating whether Unsloth fits a training pipeline
- Students learning LoRA and QLoRA with working code references
Skip it if
- Users without Python, a GPU and the Unsloth library installed, since the guidance cannot run training by itself
- Anyone expecting the skill to be current: its own notes say it was auto-generated from documentation and refreshed by re-running a scraper, so details may be outdated or incomplete
- Non-technical users looking for a finished app; it provides reference material, not a ready tool
Try asking
- “Write a QLoRA training script for Llama 3 on my dataset using Unsloth”
- “Explain how Unsloth reduces memory use compared with standard LoRA”
- “Help me debug an out-of-memory error when fine-tuning Mistral with Unsloth”
- “Suggest settings to speed up my Gemma fine-tuning run”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 3 original files, the MIT licence and an attribution note.
unsloth.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip unsloth.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip unsloth.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Verify generated code against the official Unsloth documentation, because the bundled references are auto-generated and the skill's Quick Reference section is still a placeholder.
- Give the agent your model name, GPU memory and dataset format so it can choose appropriate LoRA and batch settings.
- Test any training script on a small sample first, since the agent cannot check runtime behaviour or hardware compatibility.
What's inside
- references/index.md
- references/llms.md
- SKILL.md
Redistributed unmodified from Orchestra-Research/AI-Research-SKILLs under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.