nemotron-customize
Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or…
Skill by NVIDIA Nemotron Team <noreply@nvidia.com>
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: frontend, data, ml, productivity
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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- Secrets
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/nemotron-customize
What's inside
- Skill name
nemotron-customize- Description
- Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding tasks.
- License
- Apache-2.0
- Metadata
- author: NVIDIA Nemotron Team <noreply@nvidia.com> · version: 0.1.1
- Instructions
- 309 lines in SKILL.md · view on GitHub
Files (35)
- plugin.json · .claude-plugin/
- BENCHMARK.md
- SKILL.md
- evals.json · evals/
- ARTIFACTS.md · references/
- CATALOG.md · references/
- COMMANDS.md · references/
- HARDWARE.md · references/
- PATTERNS.md · references/
- WORKFLOW.md · references/
- PROJECT.md · references/act/
- STAGE.md · references/act/
- README.md · references/context/
- automodel-launcher-executor-modes.txt · references/context/
- automodel-pretrain.txt · references/context/
- automodel-sft-peft-core.txt · references/context/
- byob-benchmark-curator-translation.txt · references/context/
- checkpoint-conversion.txt · references/context/
- curator-data-acquisition.txt · references/context/
- curator-processing-language-quality.txt · references/context/
- curator-translation-faith.txt · references/context/
- data-designer-sdg.txt · references/context/
- eval-deploy-formats.txt · references/context/
- eval-sovereign-benchmarks.txt · references/context/
- eval-standard-nlu.txt · references/context/
- index.toml · references/context/
- mbridge-parallelism-performance.txt · references/context/
- mbridge-pretrain.txt · references/context/
- mbridge-sft.txt · references/context/
- modelopt-optimization.txt · references/context/
- nemo-rl-alignment.txt · references/context/
- nemotron-data-prep.txt · references/context/
- CALIBRATION.md · references/examples/
- skill-card.md
- skill.oms.sig
SKILL.md (first lines)
# nemotron-customize IMPORTANT: Read this file before answering any `nemotron-customize`, Nemotron customization, Curator curation, translation, SFT, PEFT, RL, conversion, optimization, checkpoint or existing/hosted-endpoint evaluation, or multi-step pipeline request. This applies whether the user names one step or asks you to compose several steps into a pipeline. Evaluation requests count even when no training is involved: "evaluate", "benchmark", "smoke test", or "score" an existing/hosted endpoint, an API/model ID, or a deployed model all route to `eval/model_eval`. Read this skill for those too. ## Purpose Turn a model-customization request into a repo-native Nemotron step pipeline. Plan the DAG, validate artifact wiring, and create only the YAML/config files needed to run existing steps. Use this skill only for inspecting, configuring, validating, running, or submitting existing Nemotron steps or multi-step training/customization pipelines. For frontend, dashboard, visualization, generic ML advice, billing/access, or unrelated coding tasks, stop with a short scope note and do not inspect the step catalog or edit files in that turn. ## Prerequisites - A checkout of the Nemotron repo with `src/nemotron/steps/` present; run from the repo root. - `uv` available to invoke `uv run nemotron steps ...`. - For remote execution: an env profile TOML (`NEMOTRON_ENV_FILE` or `env*.toml`) with a section matching the selected step. - For hosted services (translation, hosted eval): the auth environment variable expected by the step (for example `NVIDIA_API_KEY`), exported in the environment — never inlined or committed. - User-provided concrete values (model/checkpoint, data paths, output dir, hardware/GPU count) before any command is presented as runnable. ## Limitations - Does not invent new catalog steps. When no existing step, runner, recipe, CLI, or config can satisfy the request, it names the gap (Explorer mode) instead of fabricating a step. - Produces YAML/config for existing steps; new Python/shell is out of scope except in Explorer mode after the gap is approved. - Not for deployment-only/serving, frontend, dashboards, generic ML advice, or non-Nemotron tasks. - Does not guess concrete values (paths, model IDs, GPU counts, profiles); it asks or returns `Blocked` when they are missing. ## Core Rule Use bundled references first. The `references/` folder is the first decision surface for routing, artifacts, patterns, hardware heuristics, and command shape. Use `src/nemotron/steps/...` only as a live verification/fallback source when you need exact current config fields, manifests, runner imports, or details missing from bundled references. If sources disagree: 1. Checked live repo files win for exact execution. 2. Bundled references win for initial routing and planning. 3. Upstream docs/context packs are used only for exceptional code generation or library API details. ## Before You Begin - Read this `SKILL.md` workflow and the relevant bundled reference before opening repo source files. - Route from `references/CATALOG.md` and `references/ARTIFACTS.md` before any broad repo exploration. Once a route is determined, verify only the selected live step/config/env files needed for the answer. - Do not emit commands with fake paths, placeholder model IDs, guessed task IDs, guessed batch profiles, or default auth variable names presented as facts. Ask for missing concrete values or return a `Blocked` handoff. - Use `references/COMMANDS.md` as the authoritative checklist before finalizing configs or execution commands. - For pipeline requests, plan before editing. Do not create or modify files until the DAG, artifact edges, required inputs, and validation checks are stated and approved. - For one-shot command requests, prefer a complete parameterized command in one response over exploratory prose, but only after required inputs are known. If the user already provides the needed values and asks for only a command, answer with the command first and keep explanation minimal. - Output discipline (keeps responses tight): emit one command block per step, include only flags the step actually defines, and add no speculative or invented flags. Keep narrative to a few lines — the command plus the required safety/profile callouts, not a tutorial. Do not restate reference content the user did not ask for. - Do not spawn subagents for one-shot command lookup. Use the bundled command reference directly; verify only the selected step if needed. ## Safety Keep Bash scoped to repo-safe commands such as `uv run nemotron steps ...`, targeted tests, `git status/diff`, and config validation. Never run environment dumps (`env`, `printenv`, broad `export`) or commands that expose secret values. For remote submissions, destructive changes, or expensive launches, confirm before execution. When inspecting env/config files, avoid printing whole files that may contain secrets. Use targeted reads, report only section names and env-var names, and redact values for fields containing `token`, `key`, `secret`, `password`, `credential`, or `auth`. ## Reference Map | Question | Read first | Live fallback / verification | |---|---|---| | Which step or category fits? | `references/CATALOG.md` | `uv run nemotron steps list/show`, then selected `step.toml` | | Do artifacts chain? | `references/ARTIFACTS.md` | `src/nemotron/steps/types.toml` | | What run shape should I emit? | `references/COMMANDS.md` | checked-in config YAML plus active profile TOML | | Remote profile generation or selection | `references/COMMANDS.md` | active `NEMOTRON_ENV_FILE`, `env.toml`, or `env.*.toml` | | What hardware/backend should I recommend? | `references/HARDWARE.md` | selected step `[[models]]` and `[[strategies]]` | | Which cross-step guardrails apply? | `references/PATTERNS.md` | `src/nemotron/steps/patterns/<id>.md` | | How do I run the full workflow? | `references/WORKFLOW.md` | selected step configs, `step.py`, and runners | | Which upstream library API should generated code use? | `references/context/index.toml` -> matching pack | selected `step.py`, `_runners/`, upstream docs | | New project scaffold, only when existing repo code cannot support the request | `references/act/PROJECT.md` | existing repo project/recipe shape | | Per-stage code rules, only when existing repo code cannot support the request | `references/act/STAGE.md` | selected `step.py` and shared runner |
From NVIDIA/skills, Apache-2.0.
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Signals
- Stars
- 3,718
- Forks
- 457
- Open issues
- 8
- Last commit (this folder)
- Jun 4, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 0.1.1
- License
- Apache-2.0
- Repository
- github.com/NVIDIA/skills
- Website
- docs.nvidia.com/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from NVIDIA Nemotron Team <noreply@nvidia.com>
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nemotron-customize skill. Agent Mart. https://agentmart.dev/skills/nvidia-nemotron-customize (last updated 2026-10-24)