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 |
|
Slurm |
Multi-node batch jobs on HPC clusters |
8+ across nodes |
|
SkyPilot |
Cloud training (AWS, GCP, Azure) with spot pricing |
Any |
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.