Installation & Setup

The AITraining CLI is included when you install the aitraining package.

Installation

Using pip

pip install aitraining torch torchvision torchaudio

Using uv (Recommended)

uv pip install aitraining torch torchvision torchaudio

Verify Installation

Check that the CLI is working:

aitraining --version

You should see the version number printed.

First Run

Running aitraining without arguments launches the interactive wizard:

aitraining

This displays the Monostate banner and starts the configuration wizard.

GPU Setup

For GPU training, ensure you have CUDA installed and PyTorch can detect your GPU:

import torch
print(torch.cuda.is_available())  # Should print True
print(torch.cuda.device_count())  # Number of GPUs

Apple Silicon (M1/M2/M3)

On Apple Silicon Macs, MPS is used automatically:

import torch
print(torch.backends.mps.is_available())  # Should print True

Environment Variables

Common environment variables:

Variable	Description
`HF_TOKEN`	Hugging Face token for private models/datasets
`WANDB_API_KEY`	Weights & Biases API key for logging
`CUDA_VISIBLE_DEVICES`	Specify which GPUs to use

Set these before running training:

export HF_TOKEN="your_token_here"
export WANDB_API_KEY="your_key_here"

Installation & Setup

Installation & Setup

Installation

Using pip

Using uv (Recommended)

Verify Installation

First Run

GPU Setup

Apple Silicon (M1/M2/M3)

Environment Variables

Next Steps

Command Structure

LLM Training

​Installation & Setup

​Installation

​Using pip

​Using uv (Recommended)

​Verify Installation

​First Run

​GPU Setup

​Apple Silicon (M1/M2/M3)

​Environment Variables

​Next Steps

Command Structure

LLM Training

Installation & Setup

Installation

Using pip

Using uv (Recommended)

Verify Installation

First Run

GPU Setup

Apple Silicon (M1/M2/M3)

Environment Variables

Next Steps