Global Options

Options available across all CLI commands

Global Options

These options work across most AITraining CLI commands.

Version

Check the installed version:

aitraining --version
aitraining -v

Help

Get help for any command:

aitraining --help
aitraining llm --help
aitraining text-classification --help

Config File

Load parameters from a YAML configuration file:

aitraining --config path/to/config.yaml

This is useful for:

• Reproducible experiments
• Complex configurations
• Sharing settings with teammates

Backend

Specify where training runs:

aitraining llm --train --backend local ...

Available backends:

Backend	Description
local	Run on local machine (default). Variants: local-cli, local-ui
spaces-*	Run on Hugging Face Spaces
ep-*	Hugging Face Endpoints
ngc-*	NVIDIA NGC/DGX Cloud
nvcf-*	NVIDIA Cloud Functions

Spaces Backend Options

Backend	GPU
spaces-t4-small	T4 (small)
spaces-t4-medium	T4 (medium)
spaces-a10g-small	A10G (small)
spaces-a10g-large	A10G (large)
spaces-a10g-largex2	2x A10G
spaces-a10g-largex4	4x A10G
spaces-a100-large	A100
spaces-l4x1	1x L4
spaces-l4x4	4x L4
spaces-l40sx1	1x L40S
spaces-l40sx4	4x L40S
spaces-l40sx8	8x L40S
spaces-cpu-basic	CPU only
spaces-cpu-upgrade	CPU (upgraded)

Remote backends require authentication: When using non-local backends (spaces-*, ep-*, ngc-*, nvcf-*), you must provide --username and --token for Hugging Face authentication.

Push to Hub also requires authentication: Even with --backend local, using --push-to-hub requires --username and --token to upload the model to Hugging Face Hub.

Environment Variables

Set these before running commands:

Authentication

export HF_TOKEN="hf_..."        # Hugging Face token
export WANDB_API_KEY="..."       # Weights & Biases key

GPU Configuration

export CUDA_VISIBLE_DEVICES=0,1  # Use specific GPUs
export PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512  # Memory management

MPS (Apple Silicon) Control

export AUTOTRAIN_DISABLE_MPS=1  # Force CPU training on Mac
export AUTOTRAIN_ENABLE_MPS=1   # Force MPS even with quantization

Interactive Mode

Launch the configuration wizard:

aitraining           # No arguments = wizard mode
aitraining llm --interactive  # Explicit interactive mode

Next Steps

YAML Configs

Configuration file format

Command Structure

Full command reference