Guide · Agent skill
How to use the Unsloth Fine-Tuning Guide agent skill
Updated · written with AI from the project's own documentation and checked against our catalogue data
The unsloth agent skill is a documentation-based add-on that lets an AI agent answer questions about Unsloth, a library for fine-tuning open language models. Fine-tuning means training a model further on your own examples so it behaves differently. This guide is for developers, engineers and students who want the agent to suggest Unsloth code and settings for faster, lower-memory LoRA and QLoRA training. By the end you will know how to install the skill, how to ask for help with it, and what it does not do.
Unsloth Fine-Tuning GuideOrchestra-Research/AI-Research-SKILLs · MIT Download the skill Quick start
- 1Download the ZIP. Download the unsloth skill ZIP from this page.
- 2Unzip the skill folder. Unzip it so SKILL.md and the references/ folder sit together in one unsloth folder.
- 3Place the folder. Move it to ~/.claude/skills/ for personal use or to .claude/skills/ in a project.
- 4Or upload it in the apps. In the Claude apps, go to Settings → Capabilities → Skills and upload the skill.
- 5Prepare your training setup. Install Python, Unsloth and its dependencies, and confirm you have a suitable NVIDIA GPU.
- 6Ask a specific question. Describe your model, GPU, dataset and goal in plain language.
- 7Verify the answer. Check suggested code and settings against the Unsloth documentation before running them.
What is an agent skill and what does the unsloth skill do?
An agent skill is a folder of instructions and reference files that an AI agent loads when a task matches it. The unsloth skill is built around a SKILL.md file and a references/ folder that holds bundled Unsloth documentation. When you ask about Unsloth, the agent can read those files and suggest code and settings for faster training with less memory, using LoRA and QLoRA methods.
The skill is documentation only. It does not train a model, install Unsloth or run anything on your machine. The training itself happens in your own Python environment.
- Answers questions about Unsloth features and APIs
- Suggests LoRA and QLoRA settings for faster, lower-memory training
- Points to reference material for models such as Llama, Mistral, Gemma and Qwen
Install the unsloth skill from the ZIP file
Download the ZIP from this page and unzip it. The skill folder must contain SKILL.md and the references/ folder. Then place it in one of these locations:
For a personal setup, unzip it into ~/.claude/skills/. For a single project, unzip it into the project's .claude/skills/ folder.
In the Claude apps, you can instead upload the skill under Settings → Capabilities → Skills.
- Personal: ~/.claude/skills/unsloth/
- Project: .claude/skills/unsloth/ inside your project
- Claude apps: Settings → Capabilities → Skills, then upload
Trigger the skill with natural requests
You do not need a special command. The SKILL.md file lists situations where the skill should apply: working with Unsloth, asking about its features or APIs, implementing Unsloth solutions, debugging Unsloth code and learning its best practices. Ask in plain language and name Unsloth or the task so the agent recognises it.
Good requests name the model, the GPU situation and the goal. The more specific you are, the more useful the answer.
- How do I set up a LoRA fine-tune of Mistral with Unsloth on one GPU?
- Why is my Unsloth QLoRA run running out of memory?
- What do I need installed before I can fine-tune Qwen with Unsloth?
- Explain the difference between LoRA and QLoRA for a small dataset.
Check what you need before you start
The skill itself is light, but practical use needs a working training setup. The source lists a Python environment, the Unsloth library and its dependencies (torch, transformers, trl, datasets and peft), and an NVIDIA GPU suited to fine-tuning.
The bundled docs include pages on Unsloth requirements, including system and GPU VRAM requirements, and on installing and updating Unsloth. Read those pages before you start a run.
- Python environment
- Unsloth library installed
- Dependencies: torch, transformers, trl, datasets, peft
- NVIDIA GPU suited to fine-tuning
Safety notes: scripts and network access
The skill runs no scripts and uses no network access, according to its listing. It only reads its own documentation files. That means it cannot send your data anywhere or start a training job.
Any code the agent suggests is text you must review and run yourself. Check model names, package versions and dataset handling before you run it, especially on data you care about.
- Runs scripts: no
- Uses network: no
- Review all suggested code before running it
Tips for better answers
The skill's own notes say it was auto-generated from documentation and refreshed by re-running a scraper, so details may be outdated or incomplete. Treat its answers as a starting point and confirm settings against the current Unsloth docs.
Paste your error message and your environment details into the request. The agent can then match the problem to the reference pages instead of guessing.
- Include the exact error message and your library versions
- Say which GPU and how much VRAM you have
- Ask the agent to point to the reference page it used, then check it
What people use it for
- Choosing LoRA or QLoRA settings for fine-tuning a Llama or Mistral model on one GPU
- Debugging an out-of-memory error during an Unsloth training run
- Learning how LoRA and QLoRA work with working code references
- Checking whether Unsloth fits an existing training pipeline built on trl and peft
- Finding the Unsloth requirements and installation pages before a new setup
Frequently asked questions
How do I install the unsloth agent skill?
Download the ZIP from this page and unzip it so the unsloth folder contains SKILL.md and references/. Put it in ~/.claude/skills/ for personal use or in a project's .claude/skills/ folder. In the Claude apps you can also upload it under Settings → Capabilities → Skills.
Is the unsloth skill free and what licence does it use?
The skill is listed under the MIT licence. The skill listing does not state any price, so check the directory page for current terms.
What do I need to use it?
You need a Python environment, the Unsloth library and its dependencies (torch, transformers, trl, datasets, peft), and an NVIDIA GPU suited to fine-tuning. The skill gives guidance only, so it cannot train anything without this setup.
Does the skill run code or access the internet?
According to its listing, it runs no scripts and uses no network access. It reads bundled documentation files only.
Is the skill up to date with the latest Unsloth?
Not guaranteed. The skill notes say it was auto-generated from documentation and refreshed by re-running a scraper, so details may be outdated or incomplete. Confirm settings against the current Unsloth docs.
What should I use instead if I need a finished tool?
The skill is reference material, not a ready app. If you need a finished application rather than coding guidance, look for a tool built for that purpose; the Unsloth documentation itself covers installing the library and its requirements.
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Our verdict
Use the unsloth skill if you already have Python, Unsloth and an NVIDIA GPU and want an agent to help you write and tune LoRA or QLoRA training code. Pick something else if you want a finished fine-tuning app, you lack the Python and GPU setup, or you need guidance guaranteed to be current.
Download the skill