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Choosing parallelism strategies in Megatron Bridge v1.0.0

Use this resource to choose and combine parallelism strategies for Megatron Bridge training

New

  • 453 downloads
  • 209 likes
  • 240 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install parallelism-strategy-selection-guide

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent proposes a starting point from model size (dense or MoE), matches hardware topology and sequence length, computes the minimum GPU count and a memory estimate, then gives the combined configuration. You get a justified parallelism plan.

Mostly picked by

Updated November 2, 2026

Card for the “Choosing parallelism strategies in Megatron Bridge” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
Apache-2.0

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What you get

  • SKILL.md: sizing rules and examples
  • card.yaml: structured card
  • evals/evals.json: evaluation cases

Good fit for

  • You move from a 10B to a 70B model and are unsure which parallelism to use
  • You have a fixed number of GPUs and want to split them

Not for

    Tags

    • parallelism
    • TP
    • PP
    • Megatron Bridge

    About

    You say

    “Which parallelism for a dense 70B model on 64 H100 GPUs with 8K sequences?”

    Card for the “Choosing parallelism strategies in Megatron Bridge” skill

    Skill published by nvidia under the Apache-2.0 license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to choose and combine parallelism strategies for Megatron Bridge training
    3. Review and adjust the result

    Content preview

    Files

    • BENCHMARK.md4.4 KB
    • card.yaml2.9 KB
    • evals/evals.json1.5 KB
    • LICENSE11.3 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • skill-card.md3.7 KB
    • SKILL.md9.6 KB
    • skill.oms.sig4.7 KB

    Origin and licence

    Listed unmodified

    Author
    nvidia
    Source
    github.com/nvidia/skills/tree/ca116d60beafe1b4459f0ab790b7b450912c56b0/skills/nemo-mbridge-perf-parallelism-strategies
    Licence
    Apache-2.0

    Notice

    « nemo-mbridge-perf-parallelism-strategies » (nvidia, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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