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Documentation Index

Fetch the complete documentation index at: https://docs.monostate.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Installing AI Training

This guide will walk you through installing AI Training on your computer. The process takes about 5-10 minutes.

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What You’ll Get

When you install AI Training with pip or uv, you get:
  • Command Line Interface - The aitraining command for training models
  • Chat Interface - Test and interact with your trained models via browser
  • Python API - Import and use in your Python scripts
All interfaces are included in a single package installation.

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Prerequisites

Before installing AI Training, you need Python on your system. Python is a programming language that AI Training runs on.

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Check if Python is Installed

Open your terminal (Mac) or Command Prompt (Windows) and type: 
python --version
If you see a version number like Python 3.8.0 or higher, you’re good to go. AI Training requires Python 3.8 or newer (3.10+ recommended). If you get an error or have an older version, follow the installation steps below.

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Installing Python

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Windows Installation

  1. Download Python
  2. Run the Installer
    • Double-click the downloaded file
    • Important: Check “Add Python to PATH” at the bottom
    • Click “Install Now”
    • Wait for installation to complete
  3. Verify Installation
    • Open Command Prompt (search for “cmd” in Start menu)
    • Type: python --version
    • You should see the Python version
  4. Install pip (if needed)
    • pip usually comes with Python, but verify:
    pip --version
    • If not found, run:
    python -m ensurepip --upgrade

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Installing AI Training

Once Python is ready, you have two options for installing AI Training. We recommend using uv for faster installation. uv is a modern Python package installer that’s much faster than pip and handles virtual environments automatically.

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Install uv first:

# Using PowerShell (as administrator)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

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Then install AI Training:

# uv automatically creates and manages a virtual environment
uv pip install aitraining
That’s it! uv handles the virtual environment for you automatically.

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Option 2: Using pip (Traditional method)

If you prefer the traditional approach or can’t install uv:

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Step 1: Create a Virtual Environment

A virtual environment keeps AI Training’s files separate from other Python projects. 
python -m venv aitraining-env
aitraining-env\Scripts\activate
You’ll see (aitraining-env) in your terminal when the environment is active.

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Step 2: Install AI Training

pip install aitraining
This downloads and installs AI Training from PyPI with all its dependencies (including PyTorch).

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Step 3: Verify Installation

Check that everything installed correctly: 
aitraining --version
You should see the AI Training version number.

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Choose Your Interface

AI Training offers three ways to work:

Command Line

Best for trainingTrain models with commands. Good for scripts and automation.Start with: aitraining --help

Chat Interface

Best for testingTest your trained models interactively in a browser.Start with: aitraining chat

Python API

Best for developersIntegrate training into your Python applications.Start with: from autotrain.trainers.clm.params import LLMTrainingParams

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Optional Dependencies

Some features require additional packages:
FeaturePackageInstallPlatform
Faster LoRA trainingunslothpip install unslothLinux (SFT only, llama/mistral/gemma/qwen2)
Flash Attention 2flash-attnpip install flash-attnLinux (CUDA)
Distributed trainingaccelerateIncludedLinux/Mac/Windows
DeepSpeed Zero-3deepspeedpip install deepspeedLinux
4/8-bit quantizationbitsandbytesIncludedLinux only
Accelerate is required for multi-GPU and distributed training. It is included with AITraining. DeepSpeed is optional and provides Zero-3 memory optimization for very large models.
Quantization (int4/int8) only works on Linux. The bitsandbytes library required for --quantization int4 or --quantization int8 is not available on Windows or macOS.

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GPU Setup (Optional)

For NVIDIA GPU training, you may want to reinstall PyTorch with your specific CUDA version: 
# CUDA 11.8
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

# CUDA 12.1
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121

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Weights & Biases Setup (Optional)

AITraining uses W&B for logging by default. To enable: 
pip install wandb
wandb login
Or set the environment variable: WANDB_API_KEY=your_key

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Common Issues

Python isn’t in your system PATH. Try:
  • Use python3 instead of python
  • Reinstall Python and check “Add Python to PATH”
  • Manually add Python to PATH in System Environment Variables
On Mac/Linux, you might need to use sudo:
sudo pip install aitraining
Or better, use a virtual environment (shown above).
pip didn’t install with Python. Install it:
python -m ensurepip --upgrade
Or on Linux:
sudo apt install python3-pip
  • Make sure you have enough disk space (PyTorch is large)
  • Try upgrading pip first: pip install --upgrade pip
  • For GPU support, ensure CUDA drivers are installed

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Next Steps

Installation complete! Now you’re ready to train your first model:

Quick Start Tutorial

Train your first AI model in 10 minutes

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Need Help?