Peft Fine Tuning
Orchestra-Research/AI-Research-SKILLs
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods.
Add a cross-cutting decision pattern under src/nemotron/steps/patterns/.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-add-pattern -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-add-pattern --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/nemotron-add-pattern .claude/skills/nemotron-add-pattern && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "nemotron-add-pattern" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-add-pattern into .claude/skills/nemotron-add-pattern/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-add-pattern", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-add-patternType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-add-pattern -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-add-pattern --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/nemotron-add-pattern .agents/skills/nemotron-add-pattern && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nemotron-add-pattern" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-add-pattern into .agents/skills/nemotron-add-pattern/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-add-pattern", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-add-pattern -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-add-pattern --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/nemotron-add-pattern .cursor/skills/nemotron-add-pattern && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "nemotron-add-pattern" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-add-pattern into .cursor/skills/nemotron-add-pattern/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-add-pattern", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA-NeMo/Nemotron.git --path skills/nemotron-add-pattern--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-add-pattern -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-add-pattern --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/nemotron-add-pattern .gemini/skills/nemotron-add-pattern && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "nemotron-add-pattern" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-add-pattern into .gemini/skills/nemotron-add-pattern/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-add-pattern", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-add-patternInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-add-pattern -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/nemotron-add-pattern .github/skills/nemotron-add-pattern && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "nemotron-add-pattern" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-add-pattern into .github/skills/nemotron-add-pattern/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-add-pattern", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-add-pattern -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-add-pattern --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/nemotron-add-pattern .opencode/skills/nemotron-add-pattern && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "nemotron-add-pattern" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-add-pattern into .opencode/skills/nemotron-add-pattern/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-add-pattern", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
nemotron-add-patternAdd a cross-cutting decision pattern under src/nemotron/steps/patterns/.
Nemotron Add Pattern is an agent skill from NVIDIA-NeMo/Nemotron. Add a cross-cutting decision pattern under src/nemotron/steps/patterns/. Use when a recurring ML decision (tokenizer lock, eval bookends, LoRA-on-small-data, etc.) must be encoded so other skills can fire it during planning.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Fine-tuning. The repository describes itself as: Developer Asset Hub for NVIDIA Nemotron — A one-stop resource for training recipes, usage cookbooks, datasets, and full end-to-end reference examples to build with Nemotron models. The licence is Apache-2.0.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit ca8c409. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
uvFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Nemotron Add Pattern loads about 1.4k tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 734 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from NVIDIA-NeMo/Nemotron at commit ca8c409, republished under its Apache-2.0 licence (© NVIDIA-NeMo). 734 words, ~1,422 tokens.
.claude/skills/nemotron-add-pattern/SKILL.md (or your agent's skills folder).Invocation: /nemotron-add-pattern.
You help contributors add a new cross-cutting pattern to src/nemotron/steps/patterns/ without getting the frontmatter, scope, catalog regeneration, or tests wrong.
Concise. Checklist-first. Ask for missing facts before writing files.
PATTERNS.md and run testsFour phases. Always in this order.
Read these first:
src/nemotron/steps/patterns/sft-small-dataset-prefer-lora.mdsrc/nemotron/steps/PATTERNS.mdsrc/nemotron/steps/index.pytests/steps/test_patterns.pyThen ask the contributor:
[] for global)high, medium, or experimental)Use these repo conventions:
src/nemotron/steps/patterns/{id}.md.id.id, title, tags, triggers, steps, and confidence.steps: [] is valid for a global pattern.high, medium, and experimental.## When to apply, ## What to do, ## Exceptions, ## References.step.toml are a separate task. Do not edit them here.Create:
src/nemotron/steps/patterns/{id}.mdThe pattern file must contain:
id, title, tags, triggers, steps, confidence## When to apply## What to do## Exceptions## ReferencesGeneration rules:
[] only when it is truly global.What to do; keep background explanation shorter than the action guidance.When to apply.uv run python src/nemotron/steps/index.pyuv run pytest tests/steps -qCheck all of these before finishing:
steps contains only valid step idsconfidence is one of high, medium, experimentalsrc/nemotron/steps/PATTERNS.md is updateduv run pytest tests/steps -q passesIf validation fails:
Show:
steps list or global)PATTERNS.md was regenerateduv run pytest tests/steps -q passedsmall-dataset-lora.mdPATTERNS.mdstep.toml strategy blocks herehigh confidence without evidencesrc/nemotron/steps/STEPS.md and ask which ids the contributor actually wants.experimental rather than overstating certainty.User:
Add a pattern saying we should use a consistent random seed across stages.
Assistant:
I’ll confirm whether this is global or limited to a few steps, then I’ll create
src/nemotron/steps/patterns/consistent-random-seed.mdwith the required frontmatter and the four body sections.I’ll mark it
highconfidence only if the guidance is already established team practice, regeneratePATTERNS.mdwithuv run python src/nemotron/steps/index.py, and runuv run pytest tests/steps -qbefore I finish.
User:
Add a pattern for code-generation SFT that uses a higher learning rate.
Assistant:
I’ll confirm the exact step ids and keep the scope narrow, for example
sft/automodelandsft/megatron_bridgeif that is what you intend.Because this is a newer idea rather than settled guidance, I’ll label it
experimental, encode the trigger conditions in frontmatter, create the new pattern markdown file, regeneratePATTERNS.md, and runuv run pytest tests/steps -q.
© NVIDIA-NeMo, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/nemotron-add-pattern of NVIDIA-NeMo/Nemotron.
Open the folder on GitHubat commit ca8c409
Nemotron Add Pattern next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Nemotron Add Pattern this skillNVIDIA-NeMo/Nemotron | 2.1k | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Peft Fine TuningOrchestra-Research/AI-Research-SKILLs | 13k | 9 repos | ~3.1k | Automated safety check: Pass | MIT | |
| Hugging Face LLM Trainerhuggingface/skills | 11k | 3 repos | ~7.2k | Automated safety check: Pass | Apache-2.0 | |
| Sentence-Transformers Training Routerhuggingface/skills | 11k | 1 repos | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Dataset Evaluationawslabs/agent-plugins | 915 | 2 repos | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Train RlOpenPipe/ART | 11k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 |
Orchestra-Research/AI-Research-SKILLs
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods.
huggingface/skills
Trains or fine-tunes language and vision models with TRL or Unsloth on Hugging Face Jobs cloud GPUs, then converts the results to GGUF.
huggingface/skills
Routes a sentence-transformers training task to the right model type and required reference docs and example scripts, covering bi-encoders, rerankers, sparse and multi-vector models.
awslabs/agent-plugins
Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR).
OpenPipe/ART
RL training reference for the ART framework. An agent skill from OpenPipe/ART.
R6410418/Jackrong-llm-finetuning-guide
Prepare, validate, launch-plan, monitor, resume, and stop configurable Qwopus 27B reinforcement-learning workflows for GRPO or GSPO.
NVIDIA-NeMo/Nemotron
Onboard a new model family (Nemotron or third-party) into skills/ — paper chunks, recipe summaries, context packs, and model card.
NVIDIA-NeMo/Nemotron
Add a new step under src/nemotron/steps/<category/<stepid/ — manifest (step.toml), runner glue, configs, and per-step README.md.
NVIDIA-NeMo/Nemotron
Prepare, validate, build, and use Nemotron Customizer airgap image bundles for offline clusters.
NVIDIA-NeMo/Nemotron
Reference desk for Nemotron 3 Nano / Llama-Nemotron Nano 3 — architecture, training data, recipes, evaluation, quantization, deployment.
NVIDIA-NeMo/Nemotron
Reference desk for NVIDIA Nemotron 3 Super — architecture, training data, recipes (pretrain/SFT/RL/eval/quantization), and deployment notes.
NVIDIA-NeMo/Nemotron
Run the Nemotron-3.5 Lightning Text2SQL LoRA fine-tuning tutorial (NeMo Megatron-Bridge) end-to-end for the user on a single node: data prep, checkpoint conversion, LoRA fine-tuning of the 30B-A3B…
Categories
Add a cross-cutting decision pattern under src/nemotron/steps/patterns/. Nemotron Add Pattern is an agent skill from NVIDIA-NeMo/Nemotron. Add a cross-cutting decision pattern under src/nemotron/steps/patterns/.
Nemotron Add Pattern fits situations like: A recurring ML decision (tokenizer lock; loRA-on-small-data; etc.) must be encoded so other skills can fire it during planning.
Run `npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-add-pattern -a claude-code`. Or copy the skill folder (skills/nemotron-add-pattern in NVIDIA-NeMo/Nemotron) into .claude/skills/nemotron-add-pattern in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-add-pattern -a codex`. Or copy the skill folder (skills/nemotron-add-pattern in NVIDIA-NeMo/Nemotron) into .agents/skills/nemotron-add-pattern in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-add-pattern -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nemotron-add-pattern, .gemini/skills/nemotron-add-pattern, .github/skills/nemotron-add-pattern and .opencode/skills/nemotron-add-pattern in your project.
Going by SKILL.md and its folder, Nemotron Add Pattern needs the command-line tools its instructions call (uv). Our summary lists: Python 3.
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Nemotron Add Pattern is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Nemotron Add Pattern: Peft Fine Tuning (Orchestra-Research/AI-Research-SKILLs, 13k stars), Hugging Face LLM Trainer (huggingface/skills, 11k stars), Sentence-Transformers Training Router (huggingface/skills, 11k stars) and Dataset Evaluation (awslabs/agent-plugins, 915 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NVIDIA-NeMo (a GitHub organization) maintains it in NVIDIA-NeMo/Nemotron, which has 2,137 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 6, 2026.
Source: NVIDIA-NeMo/Nemotron on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.