nemo-mbridge-mlm-bridge-training skillA
nemo-mbridge-mlm-bridge-training is agent-read markdown (skill) from nvidia/skills: Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data. Covers correlation testing, available recipes, and multi-GPU examples..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# MLM vs Bridge Training For how they differ, the arg mapping tables, gotchas, and translation script, see: - @docs/megatron-lm-to-megatron-bridge.md ## First Answer Checklist For MLM-vs-Bridge correlation questions, always name these items up front: 1. Bridge recipe: `vanilla_gpt_pretrain_config`. 2. Bridge entry point: `scripts/training/run_recipe.py`. 3. MLM entry point: `3rdparty/Megatron-LM/pretrain_gpt.py`. 4. Launch wrapper for both: `uv run python -m torch.distributed.run`. 5. Fresh-run cleanup: `rm -rf nemo_experiments` before the Bridge run. Also state that MLM needs `PYTHONPATH=3rdparty/Megatron-LM:$PYTHONPATH`, matched Bridge and MLM losses should agree within BF16 rounding, and files under `3rdparty/Megatron-LM/` should not be modified from this repo. ## Correlation Testing Use `vanilla_gpt_pretrain_config` for loss-correlation testing. This recipe uses bare `GPTModelProvider` defaults (LayerNorm, GeLU, learned_absolute position embeddings, `vocab_size` inherited from tokenizer) — matching MLM `pretrain_gpt.py` defaults with no args. ### MLM Correlation Run (2L/256H, 1 GPU) ```bash PYTHONPATH=3rdparty/Megatron-LM:$PYTHONPATH \ …
Read the whole file at its exact version.
How to install
mdr add nvidia/skills/nemo-mbridge-mlm-bridge-training@git:20260716.da6c7d5mdr add nvidia/skills/nemo-mbridge-mlm-bridge-training@sha256:7eae976eb49a73e8Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_25bz7piuv2cdtb4o)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260716.da6c7d5 latest | 2026-07-16 | da6c7d5 | 6,296 B | A | view · diff |
| git:20260602.e695a83 | 2026-06-02 | e695a83 | 6,291 B | A | view · diff |
| git:20260529.7d99fda | 2026-05-29 | 7d99fda | 5,662 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (6296 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
nvidia/skills · 3,415 stars · license Apache-2.0 · pushed 2026-09-23 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_25bz7piuv2cdtb4o GET https://markdownregistry.com/api/v1/resolve?ref=nvidia/skills/nemo-mbridge-mlm-bridge-training GET https://markdownregistry.com/api/v1/blob/7eae976eb49a73e87d1e77a5295c3a79e4f1fac7a70dd0643cbffc5d4d3801c1
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