Fine-TuningFrameworks

Unsloth Documentation & Notebooks

by Unsloth

IntermediateDocumentationFreeSelf-paced

Fine-tune modern open models 2x faster with far less memory — free Colab notebooks included.

Start LearningReviewed July 3, 2026

Overview

Unsloth is a popular open-source library that makes fine-tuning dramatically faster and lighter through optimized kernels, letting you fine-tune recent open models on a free Colab GPU. The documentation is beginner-friendly and comes with a large collection of one-click notebooks for specific models and tasks (LoRA, full fine-tuning, GRPO/reasoning). It's the fastest way to go from 'I want to fine-tune Llama' to a trained model.

At a Glance

Topic
Fine-Tuning
Level
Intermediate
Format
Documentation
Cost
Free
Duration
Self-paced
Provider
Unsloth
Hands-on
Yes — code/exercises
Certificate
None

What You’ll Learn

  • Fast, low-memory fine-tuning of open models
  • Using ready-made notebooks for Llama, Mistral, Gemma, Qwen
  • LoRA and reasoning (GRPO) fine-tuning in practice
  • Exporting to GGUF/Ollama for local inference

Highlights

  • 2x faster, big memory savings
  • One-click Colab notebooks per model
  • Fine-tune on free GPUs

Who It’s For

Best For

  • Practitioners who want to fine-tune quickly and cheaply

Prerequisites

  • Basic Python
  • Comfort with notebooks

FAQ

What is Unsloth Documentation & Notebooks?

Unsloth's docs and ready-to-run notebooks for fast, memory-efficient fine-tuning of Llama, Mistral, Gemma, Qwen, and more.

Is Unsloth Documentation & Notebooks free?

Unsloth Documentation & Notebooks is free to access.

What level is Unsloth Documentation & Notebooks for?

Unsloth Documentation & Notebooks is aimed at a intermediate audience. Recommended background: Basic Python, Comfort with notebooks.

How long does Unsloth Documentation & Notebooks take?

Expect roughly Self-paced. Most learners work through it at their own pace.

What will I learn from Unsloth Documentation & Notebooks?

You'll learn: Fast, low-memory fine-tuning of open models; Using ready-made notebooks for Llama, Mistral, Gemma, Qwen; LoRA and reasoning (GRPO) fine-tuning in practice; Exporting to GGUF/Ollama for local inference.

Topics

Unslothfine-tuningLoRALlamaColab