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SkillsMP a collecté 15 skills depuis NVIDIA-NeMo/Megatron-Bridge. Ouvrez un skill pour examiner sa source et ses détails.
Affichage de 15 skills collectés sur 15.
Create or update concise, agent-readable Megatron Bridge model verification cards. Use when adding a model support card, auditing cross-model convergence comparability or verification coverage, recording conversion, deterministic inference, training,…
Langue du texte source : anglais
Structured single-agent code review workflow for PRs, commits, and local diffs. Use when asked to review code, understand a PR, rubber duck a change, prepare GitHub review comments, compare a change against Megatron Bridge conventions, or produce high-signal…
Langue du texte source : anglais
Analyze NVIDIA Nsight Systems `.nsys-rep` and exported `.sqlite` traces for Megatron Bridge training. Use for single-trace diagnosis, before/after comparisons, multi-rank surveys, slow-rank and pipeline-stage analysis, MFU or step-time investigations, GPU…
Langue du texte source : anglais
Profile, validate, and use CUDA graph capture in Megatron Bridge, including local full-iteration graphs and Transformer Engine scoped graphs. Covers replay evidence, matched eager A/Bs, model-specific scopes, regressions, and failures.
Langue du texte source : anglais
Select and validate an MoE token dispatcher (`alltoall`, DeepEP, or HybridEP) for a fixed workload and runtime. Covers backend availability, topology, matched A/B evidence, routing semantics, and failure diagnosis.
Langue du texte source : anglais
Analyze and compare PyTorch CUDA memory snapshots produced by Megatron Bridge's ProfilingConfig(record_memory_history=True). Replays the recorded allocation timeline to plot memory over time, compare two runs, and attribute peak memory to source code…
Langue du texte source : anglais
Structured framework for exact HF↔MCore weight verification, forward-pass logit correlation, and optional strict numerical diagnostics. Use when debugging weight mismatches, verifying HF↔MCore checkpoint round-trips, choosing verification tools, or…
Langue du texte source : anglais
Guide for adding support for new LLM or VLM models in Megatron-Bridge. Covers bridge, provider, recipe, tests, docs, and examples.
Langue du texte source : anglais
Testing reference for Megatron Bridge — unit and functional test layout, tier semantics (L0/L1/L2/flaky), script conventions, running tests locally, adding/moving/disabling tests, and pytest conventions.
Langue du texte source : anglais
Bump a pinned dependency (TransformerEngine, Megatron-LM, NRX, etc.), regenerate the lockfile, open a PR, and drive it to green by attaching a watchdog to the "CICD NeMo" workflow and quarantining failing functional tests as flaky until the run is green.
Langue du texte source : anglais
Dev environment setup for Megatron Bridge — container-based development, uv package management, lockfile regeneration, adding dependencies, Slurm container usage, and common build pitfalls.
Langue du texte source : anglais
CI/CD reference for Megatron Bridge — pipeline structure, commit and PR workflow, CI failure investigation, and common failure patterns.
Langue du texte source : anglais
External verl end-to-end validation workflow for Megatron-Bridge changes. Covers running a small verl Megatron backend job from a Bridge checkout, choosing LoRA/DDP plus optional save/resume and parallelism variants, setting PYTHONPATH so verl imports the…
Langue du texte source : anglais
External NeMo-RL end-to-end validation workflow for Megatron-Bridge model/provider changes, including downstream compatibility checks, external RL lifecycle behavior, Megatron policy setup, HF import/export, checkpoint/resume, non-colocated vLLM refit, delta…
Langue du texte source : anglais
Code style and quality rules for Megatron Bridge — ruff configuration, naming conventions, type hints, mypy rules, docstrings, copyright headers, logging, and the code review checklist.
Langue du texte source : anglais