Generated banner for Nemo Automodel Launcher Config
Generated logo for Nemo Automodel Launcher Config

Nemo Automodel Launcher Config

NVIDIAOfficialCreated by NVIDIA

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
  • Medium risk

From the author

Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.
— the description by NVIDIA

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The nemo-automodel-launcher-config skill provides the necessary configuration patterns for launching NeMo AutoModel jobs across different compute environments. It covers interactive local execution, batch processing on Slurm HPC clusters, and cloud-agnostic deployment via SkyPilot. The skill details how to define job parameters, manage container mounts, handle environment variables, and enable diagnostic profiling using Nsight Systems.

What it does

  • Defines YAML configurations for Slurm batch job submissions.
  • Configures cloud-agnostic job execution using SkyPilot, including spot instance support.
  • Provides settings for interactive local training runs using torchrun.
  • Manages multi-node environment variables and distributed communication settings.
  • Enables Nsight Systems profiling for Slurm-based performance diagnostics.
  • Configures container bind mounts and environment variable injection.

When to use it

  • When setting up multi-node training jobs on Slurm clusters.
  • When deploying training workloads to cloud providers via SkyPilot.
  • When debugging job submission failures or environment configuration issues.
  • When switching between interactive development and production cluster execution.
  • When profiling training performance using Nsight Systems on Slurm.

Advantages

  • Unified configuration interface for diverse compute backends.
  • Simplifies complex multi-node setup and rendezvous configuration.
  • Provides clear patterns for cost-effective spot instance usage.
  • Enables seamless transition from local debugging to large-scale cluster training.

Usage examples

“How do I configure a 2-node Slurm job for NeMo AutoModel?”
The agent provides a YAML block under the slurm key, specifying nodes: 2, ntasks_per_node, time, and other required parameters like container_image and hf_home.
“Show me how to run a training job on AWS using SkyPilot with spot instances.”
The agent provides a skypilot YAML configuration with use_spot: true, cloud: aws, and necessary setup commands, while advising on checkpoint intervals.
“How can I profile my Slurm training job?”
The agent explains how to add nsys_enabled: true to the slurm configuration block and notes that the resulting .nsys-rep file will be in the job output directory.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/nvidia/nemo-automodel-launcher-config/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip nemo-automodel-launcher-config.zip -d .agents/skills

Documentation by NVIDIA

Launcher Configuration

NeMo AutoModel supports three launch methods: interactive (torchrun), Slurm (HPC clusters), and SkyPilot (cloud-agnostic).

Instructions

For launcher questions, answer directly from this skill without inspecting the repository unless the user asks you to edit files. Keep the answer focused on the relevant launch YAML, required fields, and the expected runtime behavior.

Use these compact answer patterns for common questions:

  • Slurm multi-node: show a slurm: YAML block with job_name, nodes, ntasks_per_node, time, account or partition, container_image, hf_home, optional extra_mounts, env_vars, and master_port; explain that the launcher derives WORLD_SIZE = nodes * ntasks_per_node and sets MASTER_ADDR and MASTER_PORT.

  • SkyPilot spot: show a skypilot: YAML block with cloud, accelerators, num_nodes, use_spot: true, disk_size, region, setup, and env_vars; warn that spot instances can be preempted, set a short step_scheduler.checkpoint_interval, and resume with restore_from.path.

  • Nsight Systems on Slurm: show slurm.nsys_enabled: true alongside normal Slurm fields, say the launcher wraps the training command with nsys profile, and state that it produces a .nsys-rep report file. Treat profiling as diagnostic-only: use short profiling runs and disable it for normal production training because it adds overhead and large artifacts.

For Slurm answers, start with this minimal template and then adjust only the fields the user asked about:

slurm:
  job_name: llm_finetune
  nodes: 2
  ntasks_per_node: 8
  time: "04:00:00"
  account: my_account
  partition: batch
  container_image: nvcr.io/nvidia/nemo:dev
  hf_home: ~/.cache/huggingface
  master_port: 13742
  env_vars:
    HF_TOKEN: "${HF_TOKEN}"

For Slurm-only questions, do not discuss SkyPilot or profiling unless the user asks. For profiling questions, say the .nsys-rep report is written in the Slurm job working or output directory, using the launcher's Nsys output setting when one is configured.

Routing Boundary

Use this skill only for launch mechanics: interactive execution, Slurm, SkyPilot, containers, mounts, environment variables, rendezvous settings, and profiling.

Do not use this skill for implementing or registering new model architectures, Hugging Face state-dict adapters, model files, or capability flags. Those are model onboarding tasks, not launcher configuration tasks.

Launch Methods

  1. Interactive (default): runs torchrun on the current node. Suitable for single-node development and debugging.

  2. Slurm: submits a batch job to an HPC cluster scheduler. Handles multi-node setup, container management, and environment configuration.

  3. SkyPilot: cloud-agnostic job submission to AWS, GCP, Azure, Lambda, or Kubernetes. Supports spot instances.

Interactive Launch

# Single GPU
automodel finetune llm -c config.yaml

# Multi-GPU (all GPUs on current node)
torchrun --nproc_per_node=8 -m nemo_automodel._cli.app finetune llm -c config.yaml

No additional YAML section is needed for interactive mode. The CLI routes to torchrun automatically when no slurm: or skypilot: section is present in the config.

Slurm Configuration

The SlurmConfig dataclass generates an SBATCH script from a template.

YAML Example
slurm:
  job_name: llm_finetune
  nodes: 2
  ntasks_per_node: 8
  time: "04:00:00"
  account: my_account
  partition: batch
  container_image: nvcr.io/nvidia/nemo:dev
  hf_home: ~/.cache/huggingface
  extra_mounts:
    - source: /data
      dest: /data
  env_vars:
    WANDB_API_KEY: "${WANDB_API_KEY}"
    HF_TOKEN: "${HF_TOKEN}"
Key Fields
  • job_name: Slurm job identifier

  • nodes: number of nodes to request

  • ntasks_per_node: number of tasks (GPUs) per node

  • time: wall-time limit in HH:MM:SS format

  • account, partition: Slurm scheduling parameters

  • container_image: Enroot/Pyxis container image path

  • nemo_mount: mount point for NeMo AutoModel source inside the container

  • hf_home: HuggingFace cache directory path

  • extra_mounts: list of VolumeMapping(source, dest) for additional container bind mounts

  • master_port: port for distributed communication (default 13742)

  • env_vars: environment variables passed into the job

  • nsys_enabled: when true, wraps the training command with nsys profile for Nsight Systems profiling

SkyPilot Configuration

The SkyPilotConfig dataclass defines cloud job parameters.

YAML Example
skypilot:
  cloud: aws
  accelerators: "H100:8"
  num_nodes: 2
  use_spot: true
  disk_size: 200
  region: us-east-1
  setup: "pip install nemo-automodel"
  env_vars:
    HF_TOKEN: "${HF_TOKEN}"
Key Fields
  • cloud: target cloud provider (aws, gcp, azure, lambda, kubernetes)

  • accelerators: GPU type and count (e.g., "H100:8", "A100-80GB:4")

  • num_nodes: number of cloud instances

  • use_spot: use preemptible/spot instances for cost savings

  • disk_size: disk size in GB per node

  • region: cloud region for instance placement

  • setup: shell commands to run before the training job (e.g., install dependencies)

  • env_vars: environment variables for the job

SkyPilot spot checklist

When using spot or preemptible instances:

  • Set use_spot: true in the skypilot: section.

  • Include accelerators, num_nodes, disk_size, region, setup, and required env_vars.

  • Use short checkpoint intervals in the recipe, for example step_scheduler.checkpoint_interval, because spot instances can be preempted.

  • Resume from the most recent checkpoint after preemption with the recipe's restore_from setting.

Minimal spot-resume recipe keys:

step_scheduler:
  checkpoint_interval: 100

restore_from:
  path: /checkpoints/latest

Multi-Node Environment

For multi-node training (both Slurm and SkyPilot), the launcher automatically configures:

  • MASTER_ADDR: hostname of the first node

  • MASTER_PORT: port for rendezvous (default 13742)

  • WORLD_SIZE: total number of processes (nodes * ntasks_per_node)

  • NCCL environment variables for optimized collective communication

Nsys Profiling

Enable Nsight Systems profiling in Slurm jobs:

slurm:
  job_name: llm_profile
  nodes: 1
  ntasks_per_node: 8
  time: "00:30:00"
  account: my_account
  partition: batch
  container_image: nvcr.io/nvidia/nemo:dev
  nsys_enabled: true

This is a Slurm launcher setting. Normal Slurm fields such as job_name, nodes, ntasks_per_node, time, account or partition, and container_image still apply.

When nsys_enabled: true, the launcher wraps the training command with nsys profile and writes a .nsys-rep report file for performance analysis in the Slurm job working or output directory. Profiling is diagnostic-only: run it for a short investigation, expect overhead and large artifacts, and turn it off for normal production training.

Code Anchors

  • components/launcher/slurm/config.py - SlurmConfig dataclass, VolumeMapping

  • components/launcher/slurm/template.py - SBATCH script template generation

  • components/launcher/slurm/utils.py - Slurm submission utilities

  • components/launcher/skypilot/config.py - SkyPilotConfig dataclass

  • _cli/app.py - CLI entry point and launcher routing logic

Pitfalls

  • Port collisions: if the default master_port (13742) is in use by another job on the same node, change it to avoid connection failures.

  • Container mounts: the source path in extra_mounts must exist on all nodes in the allocation. Missing paths cause container startup failures.

  • Slurm fault tolerance: the fault tolerance plugin is Slurm-specific and does not work with SkyPilot or interactive mode.

  • SkyPilot spot preemption: spot instances (use_spot: true) may be preempted by the cloud provider. Enable checkpointing with short intervals to minimize lost work.

  • Environment variable syntax: use ${VAR} syntax in YAML for shell variable expansion. Bare variable names will not be expanded.

  • Time limit vs async checkpoint: if the Slurm time limit is too short, an in-progress async checkpoint write may be killed before completion, resulting in a corrupted checkpoint. Leave at least 5-10 minutes of margin.

Files

LICENSE

Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.


                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

   1. Definitions.

      "License" shall mean the terms and conditions for use, reproduction,
      and distribution as defined by Sections 1 through 9 of this document.

      "Licensor" shall mean the copyright owner or entity authorized by
      the copyright owner that is granting the License.

      "Legal Entity" shall mean the union of the acting entity and all
      other entities that control, are controlled by, or are under common
      control with that entity. For the purposes of this definition,
      "control" means (i) the power, direct or indirect, to cause the
      direction or management of such entity, whether by contract or
      otherwise, or (ii) ownership of fifty percent (50%) or more of the
      outstanding shares, or (iii) beneficial ownership of such entity.

      "You" (or "Your") shall mean an individual or Legal Entity
      exercising permissions granted by this License.

      "Source" form shall mean the preferred form for making modifications,
      including but not limited to software source code, documentation
      source, and configuration files.

      "Object" form shall mean any form resulting from mechanical
      transformation or translation of a Source form, including but
      not limited to compiled object code, generated documentation,
      and conversions to other media types.

      "Work" shall mean the work of authorship, whether in Source or
      Object form, made available under the License, as indicated by a
      copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object
      form, that is based on (or derived from) the Work and for which the
      editorial revisions, annotations, elaborations, or other modifications
      represent, as a whole, an original work of authorship. For the purposes
      of this License, Derivative Works shall not include works that remain
      separable from, or merely link (or bind by name) to the interfaces of,
      the Work and Derivative Works thereof.

      "Contribution" shall mean any work of authorship, including
      the original version of the Work and any modifications or additions
      to that Work or Derivative Works thereof, that is intentionally
      submitted to Licensor for inclusion in the Work by the copyright owner
      or by an individual or Legal Entity authorized to submit on behalf of
      the copyright owner. For the purposes of this definition, "submitted"
      means any form of electronic, verbal, or written communication sent
      to the Licensor or its representatives, including but not limited to
      communication on electronic mailing lists, source code control systems,
      and issue tracking systems that are managed by, or on behalf of, the
      Licensor for the purpose of discussing and improving the Work, but
      excluding communication that is conspicuously marked or otherwise
      designated in writing by the copyright owner as "Not a Contribution."

      "Contributor" shall mean Licensor and any individual or Legal Entity
      on behalf of whom a Contribution has been received by Licensor and
      subsequently incorporated within the Work.

   2. Grant of Copyright License. Subject to the terms and conditions of
      this License, each Contributor hereby grants to You a perpetual,
      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
      copyright license to reproduce, prepare Derivative Works of,
      publicly display, publicly perform, sublicense, and distribute the
      Work and such Derivative Works in Source or Object form.

   3. Grant of Patent License. Subject to the terms and conditions of
      this License, each Contributor hereby grants to You a perpetual,
      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
      (except as stated in this section) patent license to make, have made,
      use, offer to sell, sell, import, and otherwise transfer the Work,
      where such license applies only to those patent claims licensable
      by such Contributor that are necessarily infringed by their
      Contribution(s) alone or by combination of their Contribution(s)
      with the Work to which such Contribution(s) was submitted. If You
      institute patent litigation against any entity (including a
      cross-claim or counterclaim in a lawsuit) alleging that the Work
      or a Contribution incorporated within the Work constitutes direct
      or contributory patent infringement, then any patent licenses
      granted to You under this License for that Work shall terminate
      as of the date such litigation is filed.

   4. Redistribution. You may reproduce and distribute copies of the
      Work or Derivative Works thereof in any medium, with or without
      modifications, and in Source or Object form, provided that You
      meet the following conditions:

      (a) You must give any other recipients of the Work or
          Derivative Works a copy of this License; and

      (b) You must cause any modified files to carry prominent notices
          stating that You changed the files; and

      (c) You must retain, in the Source form of any Derivative Works
          that You distribute, all copyright, patent, trademark, and
          attribution notices from the Source form of the Work,
          excluding those notices that do not pertain to any part of
          the Derivative Works; and

      (d) If the Work includes a "NOTICE" text file as part of its
          distribution, then any Derivative Works that You distribute must
          include a readable copy of the attribution notices contained
          within such NOTICE file, excluding those notices that do not
          pertain to any part of the Derivative Works, in at least one
          of the following places: within a NOTICE text file distributed
          as part of the Derivative Works; within the Source form or
          documentation, if provided along with the Derivative Works; or,
          within a display generated by the Derivative Works, if and
          wherever such third-party notices normally appear. The contents
          of the NOTICE file are for informational purposes only and
          do not modify the License. You may add Your own attribution
          notices within Derivative Works that You distribute, alongside
          or as an addendum to the NOTICE text from the Work, provided
          that such additional attribution notices cannot be construed
          as modifying the License.

      You may add Your own copyright statement to Your modifications and
      may provide additional or different license terms and conditions
      for use, reproduction, or distribution of Your modifications, or
      for any such Derivative Works as a whole, provided Your use,
      reproduction, and distribution of the Work otherwise complies with
      the conditions stated in this License.

   5. Submission of Contributions. Unless You explicitly state otherwise,
      any Contribution intentionally submitted for inclusion in the Work
      by You to the Licensor shall be under the terms and conditions of
      this License, without any additional terms or conditions.
      Notwithstanding the above, nothing herein shall supersede or modify
      the terms of any separate license agreement you may have executed
      with Licensor regarding such Contributions.

   6. Trademarks. This License does not grant permission to use the trade
      names, trademarks, service marks, or product names of the Licensor,
      except as required for reasonable and customary use in describing the
      origin of the Work and reproducing the content of the NOTICE file.

   7. Disclaimer of Warranty. Unless required by applicable law or
      agreed to in writing, Licensor provides the Work (and each
      Contributor provides its Contributions) on an "AS IS" BASIS,
      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
      implied, including, without limitation, any warranties or conditions
      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
      PARTICULAR PURPOSE. You are solely responsible for determining the
      appropriateness of using or redistributing the Work and assume any
      risks associated with Your exercise of permissions under this License.

   8. Limitation of Liability. In no event and under no legal theory,
      whether in tort (including negligence), contract, or otherwise,
      unless required by applicable law (such as deliberate and grossly
      negligent acts) or agreed to in writing, shall any Contributor be
      liable to You for damages, including any direct, indirect, special,
      incidental, or consequential damages of any character arising as a
      result of this License or out of the use or inability to use the
      Work (including but not limited to damages for loss of goodwill,
      work stoppage, computer failure or malfunction, or any and all
      other commercial damages or losses), even if such Contributor
      has been advised of the possibility of such damages.

   9. Accepting Warranty or Additional Liability. While redistributing
      the Work or Derivative Works thereof, You may choose to offer,
      and charge a fee for, acceptance of support, warranty, indemnity,
      or other liability obligations and/or rights consistent with this
      License. However, in accepting such obligations, You may act only
      on Your own behalf and on Your sole responsibility, not on behalf
      of any other Contributor, and only if You agree to indemnify,
      defend, and hold each Contributor harmless for any liability
      incurred by, or claims asserted against, such Contributor by reason
      of your accepting any such warranty or additional liability.

   END OF TERMS AND CONDITIONS

   APPENDIX: How to apply the Apache License to your work.

      To apply the Apache License to your work, attach the following
      boilerplate notice, with the fields enclosed by brackets "[]"
      replaced with your own identifying information. (Don't include
      the brackets!)  The text should be enclosed in the appropriate
      comment syntax for the file format. We also recommend that a
      file or class name and description of purpose be included on the
      same "printed page" as the copyright notice for easier
      identification within third-party archives.

   Copyright [yyyy] [name of copyright owner]

   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Python, Needs Node.js

Security

What our scanner noticed· Medium risk

  • Large base64-encoded blobs
  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
NVIDIA
Publisher
NVIDIA (Official)
Source
NVIDIA/skills · skills/nemo-automodel-launcher-config · commit fce3cca
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE-APACHE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by NVIDIA or NVIDIA.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download nemo-automodel-launcher-config.zip