> This page is for version 0.6.0.
> For other versions, use one of these documentation indexes:
> - Main (default): https://docs.nvidia.com/nemo/gym/main/llms.txt
> - 0.7.0: https://docs.nvidia.com/nemo/gym/v0.7.0/llms.txt
> - 0.6.0: https://docs.nvidia.com/nemo/gym/v0.6.0/llms.txt
> - 0.5.1: https://docs.nvidia.com/nemo/gym/v0.5.1/llms.txt
> - 0.5.0: https://docs.nvidia.com/nemo/gym/v0.5.0/llms.txt
> - 0.4.0: https://docs.nvidia.com/nemo/gym/v0.4.0/llms.txt
> - 0.3.0: https://docs.nvidia.com/nemo/gym/v0.3.0/llms.txt
> - 0.2.1: https://docs.nvidia.com/nemo/gym/v0.2.1/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/gym/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/gym/_mcp/server.

# Unsloth

This tutorial demonstrates how to use [Unsloth](https://github.com/unslothai/unsloth) to fine-tune models with NeMo Gym environments.

**Unsloth** is a fast, memory-efficient library for fine-tuning large language models. It provides optimized implementations that significantly reduce memory usage and training time, making it possible to fine-tune larger models on consumer hardware.

## Prerequisites

* A Google account (for Colab) or a local GPU with 16GB+ VRAM
* Familiarity with NeMo Gym concepts ([About](/about/concepts))

The NeMo Gym integration with Unsloth is tested on `unsloth==2026.1.4` and `unsloth_zoo==2026.1.4`. Other versions are not guaranteed to work.

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## Getting Started

Follow these interactive notebooks to train models with Unsloth and NeMo Gym:

[Sudoku](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/NeMo-Gym-Sudoku.ipynb)

[Multi-Environment Training](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/NeMo-Gym-Multi-Environment.ipynb)

Check out [Unsloth's documentation](https://docs.unsloth.ai/models/nemotron-3#reinforcement-learning--nemo-gym) for more details.