Job Launchers#

NeMo AutoModel provides several ways to launch training. The right choice depends on your hardware and environment.

Which Launcher Should I Use?#

Launcher

Best for

GPUs

Guide

Local Workstation

Getting started, debugging, single-node training

1-8 on one machine

Local Workstation

Slurm

Multi-node batch jobs on HPC clusters

8+ across nodes

Slurm

SkyPilot

Cloud training (AWS, GCP, Azure) with spot pricing

Any

SkyPilot

I have 1-2 GPUs on my workstation#

Use the interactive launcher. No scheduler or cluster software needed:

automodel examples/llm_finetune/llama3_2/llama3_2_1b_squad.yaml

See the Local Workstation guide.

I have access to a Slurm cluster#

Add a slurm: section to your YAML config and submit with the same automodel command. The CLI generates the torchrun invocation and calls sbatch for you:

automodel config_with_slurm.yaml

See the Slurm guide.

I want to train on the cloud#

Add a skypilot: section to your YAML config. SkyPilot provisions VMs on any major cloud and handles spot-instance preemption automatically:

automodel config_with_skypilot.yaml

See the SkyPilot guide.

All Launchers Use the Same Config#

Every launcher shares the same YAML recipe format. The only difference is an optional launcher section (slurm: or skypilot:) that tells the CLI where to run. Without a launcher section, training runs interactively on the current machine.