unsloth

Fine-tune LLMs with Unsloth using LoRA and QLoRA techniques.

Updated Apr 29, 2026

Search Tags:#llm #fine-tuning #lora #qlora #unsloth #memory efficient #fast training

Ready to run

npx skills add https://github.com/fikriaf/agentos --skill unsloth-fikriaf

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: unsloth
Source: https://github.com/fikriaf/agentos/tree/main/src/agentos/skills/mlops/training/unsloth
Command: npx skills add https://github.com/fikriaf/agentos --skill unsloth-fikriaf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires unsloth, torch, transformers, trl, datasets, peft, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This skill provides expert guidance for fast fine-tuning with Unsloth, optimizing training speed and efficiency.

Core Features & Use Cases

Fast Fine-Tuning: Accelerates training by 2-5x with 50-80% less memory usage.
LoRA/QLoRA Optimization: Optimizes model fine-tuning with LoRA and QLoRA techniques.
Documentation & Resources: Includes comprehensive documentation and resources for Unsloth development.

Quick Start

To start using the unsloth skill, first install the Unsloth library using the command: pip install unsloth.

Frequently Asked Questions about unsloth

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I speed up LLM fine-tuning and reduce memory usage?▼

Fast LLM fine-tuning using Unsloth accelerates training by 2-5x and cuts memory usage by 50-80%. It provides expert guidance for optimizing model training performance and efficiency.

What is the best way to apply LoRA and QLoRA techniques for model training?▼

LoRA and QLoRA optimization for model fine-tuning is best handled using Unsloth. It provides expert guidance for these specific techniques alongside performance optimization.

Do I need PyTorch and Transformers to start fast fine-tuning?▼

Yes, fast fine-tuning requires Python libraries including torch, transformers, trl, datasets, and peft. You must install the Unsloth library via pip before optimizing your LLM training.

Can I use Unsloth for large language model development and training optimization?▼

Yes, Unsloth applies directly to LLM fine-tuning scenarios, model training optimization, and LLM development. It provides comprehensive documentation and resources for development workflows.

Why does LLM fine-tuning consume so much memory and how can I fix it?▼

LLM fine-tuning often consumes excessive memory, but Unsloth solves this by optimizing training to use 50-80% less memory. It accelerates training speed by 2-5x using LoRA and QLoRA.