nemo-mbridge-perf-sequence-packing
CommunityFine-tune Megatron-Bridge sequence packing workflows.
Software Engineering#finetuning#long-context#vlm#sequence-packing#packed-sequences#context-parallel#nemo-mbridge
Authorsayalinvidia
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill guides configuring and validating packed sequence paths and long-context training in Megatron-Bridge, distinguishing offline packed SFT for LLMs from in-batch packing for VLMs, and applying the correct CP constraints.
Core Features & Use Cases
- Offline packed SFT configuration via PackedSequenceSpecs to support long sequences during finetuning.
- In-batch packing for VLM finetuning and how to switch between packing modes.
- Context-parallelism padding rules, CUDA-graph metadata requirements, and finetuning prerequisites handling.
Quick Start
Provide a Megatron-Bridge training config that enables offline packed SFT with appropriate PackedSequenceSpecs and CP settings.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: nemo-mbridge-perf-sequence-packing Download link: https://github.com/sayalinvidia/sayali-skills-test/archive/main.zip#nemo-mbridge-perf-sequence-packing Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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