Menu

Individual skill

digital-health-clinical-asr-finetune

0upvotes

Stage 4 of the Clinical ASR Flywheel. Use when priority KER is above 0.3 to run stock NeMo SFT on Parakeet TDT v2 and offline cycle N+1 re-eval. NOT for generic word boosting (use /finetune-asr).

skills/digital-health-clinical-asr-finetune/SKILL.md

Read pinned source

Source commit 25340619336e89bcc40365c28bfe9e790430468e

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
No
Repository scan complete
No
Skill scan complete
No
Observed behavior
Not checked yet
Last checked
Nov 2, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
3,901
Repository last updated
Nov 6, 2026
License
Apache-2.0

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

<!--
SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
SPDX-License-Identifier: Apache-2.0
-->

# Clinical ASR Flywheel — Stage 4 (Fine-tune)

> **⚠ Agent: read this entire SKILL.md before answering.** The Critical-workflow-rules section, the base-model table (§4c), the stock-NeMo-SFT recipe (§4d), and the cycle-N+1 decision table (§4e) are all load-bearing — the do-not-SFT bases and broken-adapter warnings live there.

> **Agent: this file is self-contained.** The Stage 4 gate criteria, base-model recommendation, hyperparameter table, container invocation pattern, and cycle-N+1 decision table are all below. **Do not** run file-discovery commands or open `references/stage4-finetune.md` before answering methodology questions — the reference is deep-dive material, not required reading. Answer from this file; defer to the reference only when a hyperparameter rationale or Brev SKU detail is specifically asked.

You are the **adapt-and-measure** stage. The user arrives from `/digital-health-clinical-asr-eval` with a manifest, a baseline KER number, and the decision-tree's recommendation that fine-tuning is worth the GPU time. You run stock NeMo SFT, do an offline cycle N+1 re-eval to **measure that the loop closed**, and optionally hand the resulting `.nemo` to `/riva-asr-custom` for production serving.

**The cycle KER from offline eval is the measurement that closes the loop.** Riva NIM deploy validates serving (latency, streaming, scale), not model quality.