Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add NVIDIA-NeMo/Megatron-Bridge --skill nemo-mbridge-multi-node-slurmgit clone --depth 1 https://github.com/NVIDIA-NeMo/Megatron-BridgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nvidia-nemo/megatron-bridge/nemo-mbridge-multi-node-slurm)<a href="https://agentmods.dev/skills/nvidia-nemo/megatron-bridge/nemo-mbridge-multi-node-slurm"><img src="https://agentmods.dev/badge/skills/nvidia-nemo/megatron-bridge/nemo-mbridge-multi-node-slurm/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nvidia-nemo/megatron-bridge/nemo-mbridge-multi-node-slurm"><img src="https://agentmods.dev/badge/skills/nvidia-nemo/megatron-bridge/nemo-mbridge-multi-node-slurm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.04329 |
| Opus 5 | $0.00030 | $0.02165 |
| Sonnet 5 | $0.00012 | $0.00866 |
| Haiku 4.5 | $0.00006 | $0.00433 |
Grade C, and why
nemo-mbridge-multi-node-slurm scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
4. **Bridge `rm -rf nemo_experiments`**: Add before training to avoid stale checkpoint auto-resume. This is a copy
100% identical to nemo-mbridge-multi-node-slurm — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Node Slurm
Convert single-node uv run python -m torch.distributed.run commands into multi-node Slurm sbatch scripts with Enroot container support, and debug common multi-node failures.
First Answer Checklist
When converting or debugging Bridge multi-node jobs, answer in this order:
- Prefer the srun-native launch shape for Bridge scripts that reach
initialize.py:#SBATCH --ntasks-per-node=8and a directsrun ... uv run python <script> ...launch. Do not wrap these jobs inpython -m torch.distributed.run. - State that Bridge derives
RANK,WORLD_SIZE,LOCAL_RANK,MASTER_ADDR, andMASTER_PORTfrom SLURM variables duringinitialize.pydistributed init. - Require shared paths and matching container mounts for the repo, data, logs,
HF_HOME,UV_CACHE_DIR, andNEMO_HOME. - For NCCL timeout reports, do these first-log checks before speculating:
- grep for real errors while filtering warning/frame noise
- inspect
Failures:to find the first failed rank and node - grep for
ncclUniqueId,timeout, orcrash on rank 0
Two Approaches: srun-native vs uv run torch.distributed
| Approach | ntasks-per-node |
Process spawning | Best for |
|---|---|---|---|
| srun-native (preferred) | 8 | Slurm spawns 8 tasks/node | Conversion, inference, Bridge scripts |
| uv run torch.distributed (legacy) | 1 | uv run python -m torch.distributed.run spawns 8 procs/node |
MLM pretrain_gpt.py |
Prefer srun-native — simpler, avoids shell escaping issues with TRAIN_CMD. Megatron Bridge auto-derives RANK, WORLD_SIZE, LOCAL_RANK, MASTER_ADDR, MASTER_PORT from SLURM env vars (SLURM_PROCID, SLURM_NTASKS, SLURM_LOCALID, SLURM_NODELIST) via common_utils.py helpers called during initialize.py distributed init, so you never need to set them manually.
Cluster Environment
Use a shared filesystem for the repository, data, logs, HF_HOME, UV_CACHE_DIR, and NEMO_HOME. NEMO_HOME must not use the container-local default (/root/.cache/nemo) for multi-node SFT/PEFT jobs, because packed-sequence data prepared on node 0 must be visible to the other nodes.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 361 lines · 61 tokens per session scan C 1755991a2310
nemo-mbridge-multi-node-slurm is a skill published in the GitHub repository NVIDIA-NeMo/Megatron-Bridge (904 stars, last pushed today), licensed Apache-2.0. It adds 61 tokens to every session and 4,329 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). It is 100% identical to nemo-mbridge-multi-node-slurm, differing in 0 lines, and is treated as a copy.
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