Command Structure

The AITraining CLI follows a consistent pattern for all commands.

Basic Syntax

aitraining <command> [options]

Available Commands

Command	Description
`llm`	Train large language models (LLMs)
`chat`	Launch chat interface for inference
`api`	Start the training API server
`text-classification`	Train text classification models
`text-regression`	Train text regression models
`image-classification`	Train image classification models
`image-regression`	Train image regression models
`token-classification`	Train NER/token classification
`seq2seq`	Train sequence-to-sequence models
`tabular`	Train tabular data models
`sentence-transformers`	Train sentence embedding models
`object-detection`	Train object detection models
`vlm`	Train vision-language models
`extractive-qa`	Train extractive QA models
`tools`	Utility tools: `merge-llm-adapter`, `convert_to_kohya`
`setup`	Initial setup and configuration
`spacerunner`	Run training on Hugging Face Spaces

SpaceRunner requirements: The spacerunner command requires --project-name, --script-path, --username, --token, and --backend to be specified.

Getting Help

General Help

aitraining --help

Command-Specific Help

aitraining llm --help

Trainer-Specific Help

For LLM training, see parameters for a specific trainer:

aitraining llm --trainer sft --help
aitraining llm --trainer dpo --help
aitraining llm --trainer orpo --help
aitraining llm --trainer ppo --help

Or use preview mode:

aitraining llm --preview-trainer dpo --help

Global Options

These options are truly global (work at the top level):

Option	Description
`--help`, `-h`	Show help message
`--version`, `-v`	Show version
`--config`	Load from YAML config file

The --backend option is available on most training commands but is registered per-command, not globally. See Global Options for backend details.

Config File Usage

Instead of command-line arguments, use a YAML config:

aitraining --config training_config.yaml

Examples

Basic LLM Training

aitraining llm --train \
  --model google/gemma-3-270m \
  --data-path ./data \
  --project-name my-model \
  --trainer sft

With LoRA

aitraining llm --train \
  --model meta-llama/Llama-3.2-1B \
  --data-path ./data \
  --project-name my-lora-model \
  --peft \
  --lora-r 16 \
  --lora-alpha 32

Text Classification

aitraining text-classification \
  --model bert-base-uncased \
  --data-path ./reviews.csv \
  --text-column text \
  --target-column label \
  --project-name sentiment-model

Interactive Mode

Run without arguments to start the interactive wizard:

aitraining

Or explicitly:

aitraining llm --interactive

CLI Basics

Configuration

Training Commands

Advanced Usage

Inference

Command Structure

Command Structure

Basic Syntax

Available Commands

Getting Help

General Help

Command-Specific Help

Trainer-Specific Help

Global Options

Config File Usage

Examples

Basic LLM Training

With LoRA

Text Classification

Interactive Mode

Next Steps

LLM Training

YAML Configs

​Command Structure

​Basic Syntax

​Available Commands

​Getting Help

​General Help

​Command-Specific Help

​Trainer-Specific Help

​Global Options

​Config File Usage

​Examples

​Basic LLM Training

​With LoRA

​Text Classification

​Interactive Mode

​Next Steps

LLM Training

YAML Configs

Command Structure

Basic Syntax

Available Commands

Getting Help

General Help

Command-Specific Help

Trainer-Specific Help

Global Options

Config File Usage

Examples

Basic LLM Training

With LoRA

Text Classification

Interactive Mode

Next Steps