nemotron-asr-finetune
Orchestration skill for NVIDIA Nemotron Speech (Riva) / NeMo ASR domain and language adaptation. Given a goal like "improve/fine-tune ASR for my domain or language", it scopes the task, picks the cheapest sufficient path (word boosting → n-gram LM → fine-tuning), delegates each stage to the right sub-skill (data generation, training, evaluation, deployment), and answers cost/time/data questions along the way.
npx skills add NVIDIA/skills --skill nemotron-asr-finetune --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Nemotron Speech ASR Customization — Orchestration Skill > **Note:** "Nemotron Speech" is the public-facing name for what NVIDIA documents today as **Riva** / **Riva NIM**; the acoustic models are trained and fine-tuned with **NVIDIA NeMo**. Commands, config paths, imports, and doc URLs still use **"Riva"** / **"NeMo"** — the rename is brand-only. Do not rename them. ## What This Skill Is This is
What does the nemotron-asr-finetune skill do?
Orchestration skill for NVIDIA Nemotron Speech (Riva) / NeMo ASR domain and language adaptation. Given a goal like "improve/fine-tune ASR for my domain or language", it scopes the task, picks the cheapest sufficient path (word boosting → n-gram LM → fine-tuning), delegates each stage to the right sub-skill (data generation, training, evaluation, deployment), and answers cost/time/data questions along the way.
How do I install it?
Run `npx skills add NVIDIA/skills --skill nemotron-asr-finetune --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From NVIDIA/skills, a repository with 2,789 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.