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Research: shipped offline ASR runtimes and checkpoints: versions, licences and revision pinning

Status: Research note (not a decision). ADR-030 freeze unchanged; no default, dependency, pin or engine is changed and no new engine is proposed. Issue: NEXT-ASR-01 #792; parent #787; numeric claims belong to #793. Snapshot: YazSes main at 4695e49adb368c048f156b9aff4a9d079d6260db; upstream metadata read 2026-11-06. Complements, does not repeat: the 2026-11-03 runtime/provenance snapshot, which surveys candidate runtimes (NeMo-Speech.cpp, parakeet.cpp, Moonshine Voice) and the Parakeet v2/v3 and Nemotron licences. This note covers what that one did not: the versions YazSes actually resolves today for its four shipped ASR packages, compared with the current upstream release, and the exact checkpoint each shipped engine downloads with its licence and whether it is pinned to a revision. docs/models.md states that it does not record these details. Not done: no model or wheel was installed or run and no benchmark was taken. This note contains no WER, latency or memory numbers. Upstream metadata was read through the public PyPI JSON API, the Hugging Face model API, the GitHub REST API and one PyPI source distribution (onnx-asr 0.12.0), which was unpacked and read.

Evidence labels

  • [Fact]: read directly from a primary source (YazSes source at the snapshot, uv.lock, the PyPI/Hub/GitHub API response, the published sdist or wheel) on the date above. Upstream values can change after that date.
  • [Vendor claim]: an upstream statement about its own software that YazSes has not tested.
  • [Theory]: an inference from facts, not checked by running anything.
  • [Unverified]: open, with what would settle it.

1. Packages: declared floor vs locked vs current upstream

Package How YazSes gets it Floor in pyproject.toml Resolved in uv.lock Current on PyPI (upload date) Licence (PyPI metadata) Delta
faster-whisper base dependency >=1.2.1 1.2.1 1.2.1 (2025-10-31) MIT none
ctranslate2 transitive, through faster-whisper (ctranslate2<5,>=4.0) none of its own 4.8.1 4.8.5 (2026-11-02) MIT 4 patch releases behind
onnx-asr parakeet extra, onnx-asr[cpu,hub] >=0.12 0.12.0 0.12.0 (2026-07-15) MIT none (unreleased main work below)
useful-moonshine-onnx moonshine extra >=20251121 20251121 20251121 (2025-11-21) MIT none
onnxruntime transitive (onnx-asr, useful-moonshine-onnx, faster-whisper); declared directly in the tts, silero and all extras >=1.27.0; >=1.23.2,<1.24 on Intel macOS 1.28.0; 1.23.2 on Intel macOS 1.31.1 (2026-10-26) MIT 3 minor releases behind (Intel macOS cap is deliberate)

All values in this table are [Fact]. Sources: the [[package]] entries in uv.lock; pyproject.toml lines 70, 201–208 and 287–301; and https://pypi.org/pypi/<name>/json for each package. The licences are PyPI's license / license_expression fields, not a reading of each project's LICENSE file. The installed .venv dist-info for faster-whisper, ctranslate2 and useful-moonshine-onnx reports the same versions and the same MIT licence. onnx-asr is not installed in the base venv.

Notes on the deltas:

  • ctranslate2 4.8.1 → 4.8.5. The v4.8.5 release notes are [Vendor claim]. Their new features cover "Drama 3" prompt caching and voice cloning. The fixes are CUDA FP16/BF16 attention precision, a caching-allocator shutdown crash, and an eole converter fix (release page). [Theory] None of these targets the CPU int8 Whisper path YazSes uses by default. [Unverified] I did not read the 4.8.2–4.8.4 notes. Before calling the lag harmless, read them and run the full suite on a refreshed lock.
  • onnxruntime 1.28.0 → 1.31.1. [Fact] 1.31.1 still declares requires_python >=3.11, so the project's Python floor does not block it. The Intel macOS cap below 1.24 is documented in pyproject.toml: upstream stopped publishing an x86_64 macOS wheel after 1.23.0. That cap is a compatibility pin, not a lag. [Unverified] Whether anything in this lock holds the other platforms at 1.28.0, or the lock simply has not been refreshed. Running uv lock --upgrade-package onnxruntime in a throwaway checkout would answer it. That step is the coordinator's or owner's, because workers may not change uv.lock.
  • onnx-asr, unreleased. [Fact] On main, commit 6e63052 (2026-10-21, "Add subfolder and revision support for model loading") adds revision= and subfolder= keywords to onnx_asr.load_model. [Fact] The released 0.12.0 sdist's load_model (src/onnx_asr/loader.py:306) has neither keyword, and it has no offline= either. Its resolver supports offline mode internally (resolver.py:48–77), but load_model does not pass it through. That matches the stt/parakeet.py comment that "onnx_asr.load_model exposes no offline switch", and it is why YazSes wraps the load in system/hfcache.load_cache_first.
  • useful-moonshine-onnx dependencies. [Fact] Its PyPI requires_dist and the uv.lock entry both list huggingface-hub, librosa, numba, onnxruntime and tokenizers. The comment above the moonshine extra (pyproject.toml:295) says "onnxruntime + tokenizers only — no torch, no numpy ceiling". The "no torch" part holds. The "only" part does not: librosa and numba come in as well. That is a comment correction for whoever owns pyproject.toml; this note does not change it.

2. Checkpoints the shipped engines actually download

Engine (config value) YazSes default name Hub repository the library resolves Hub commit at read (last modified) Model-card licence Pinned to a revision by YazSes?
faster-whisper base.en (stt/decoder_settings.py:40) Systran/faster-whisper-base.en (stt/download.py:49; faster-whisper's own utils._MODELS has the same mapping) 3d3d5dee26484f91867d81cb899cfcf72b96be6c (2023-11-23) MIT No
parakeet nemo-parakeet-tdt-0.6b-v2 (stt/parakeet.py:39) istupakov/parakeet-tdt-0.6b-v2-onnx (onnx-asr 0.12.0 resolver.py:29), an ONNX conversion whose card names base_model: nvidia/parakeet-tdt-0.6b-v2 0bbb45a3365852604aef28b538a8f066f4ccaa85 (2026-02-17); base model ae9ad07059c7c739ffaf932226a8fe64ae2620b0 (2026-06-29) CC-BY-4.0 (conversion and base) No
moonshine moonshine/base (stt/moonshine.py:46) UsefulSensors/moonshine, subfolder onnx/merged/base/float (hard-coded in moonshine_onnx/model.py, 20251121). The Hub API now answers Temporary Redirect … /api/models/moonshine-ai/moonshine 48b4e427b587bcf67797a5be706d6ddc4a298149 (2025-11-30, at moonshine-ai/moonshine) MIT No

Every cell is [Fact]: commit hashes, dates and licences come from https://huggingface.co/api/models/<repo> (the sha, lastModified and license: tag / cardData.license). The commit hash is the repository's head on the read date, not necessarily the commit an existing user's cache holds.

Points that follow from the table:

  1. No shipped checkpoint is pinned. [Fact] stt/faster_whisper.py, stt/parakeet.py, stt/moonshine.py and stt/download.py never pass a revision, so every first download takes the repository's default branch. Cache-first loading (system/hfcache.py) then keeps whatever was fetched. [Theory] Two users who installed on different dates can therefore run different weights under the same engine name with no visible signal. The risk differs by engine. The Systran repo has not changed since 2023. The Parakeet conversion repo changed in February 2026 and its NVIDIA base in June 2026. Moonshine's repo has changed owner.
  2. What each library allows today. [Fact] faster-whisper 1.2.1 WhisperModel accepts revision= (faster_whisper/transcribe.py:632). onnx-asr 0.12.0 load_model does not (it is unreleased on main). useful-moonshine-onnx 20251121 calls hf_hub_download with no revision and exposes no parameter for one. So of the three shipped engines, only the Whisper path can be revision-pinned without upstream changes. [Theory] Pinning in the product is a behaviour change: existing caches would need a migration story, and choosing a revision is a maintainer decision. It is not proposed here. The low-cost step that stays in scope is for the #793 evaluation manifest to record the resolved snapshot commit and file digests per run. The 2026-11-03 note already requires that.
  3. The Moonshine repository redirect. [Fact] A request to UsefulSensors/moonshine is redirected to moonshine-ai/moonshine. [Unverified] Whether huggingface_hub.hf_hub_download, at the version in the lock (1.23.0), follows that redirect for file downloads in a fresh cache, and whether an existing cache stored under the old repo name keeps working, has not been tested. A download test in an isolated HF_HOME would settle both. If the Hub ever drops the redirect, stt-moonshine first-time setup breaks with no change on YazSes's side.
  4. The Whisper weight licence is stated two ways upstream. [Fact] The Systran conversion card says MIT. The openai/whisper-base.en Hub card carries an apache-2.0 tag. The openai/whisper GitHub repository LICENSE is MIT (GitHub licence API, spdx_id: MIT). [Unverified] Which statement governs the weights is a legal question, not an engineering one. YazSes does not redistribute weights, because the user's machine downloads them from the Hub, so this only matters if bundling weights is ever proposed.
  5. The Parakeet weights are CC-BY-4.0. [Fact] Both the conversion and the NVIDIA base model are CC-BY-4.0, which requires attribution. [Theory] YazSes does not redistribute them, so it has no attribution duty today. The research page docs/research/voice-control.md already labels Parakeet "CC-BY-4.0". Any future bundling or mirroring would need an attribution notice; see the requirements table in the 2026-11-03 note.

3. What this changes, and for whom

No product change is proposed and no engine is recommended. Items for the coordinator or owner, all outside this note's write scope:

# Item Kind Who
1 Refresh uv.lock for ctranslate2 (4.8.1 → 4.8.5) and onnxruntime (1.28.0 → 1.31.1, except the Intel macOS fork) under the "latest stable" dependency rule, then run the full suite and the FreeBSD missing-deps simulation lock refresh coordinator / owner
2 Correct the moonshine extra comment (pyproject.toml:295): the package also pulls librosa, numba and huggingface-hub comment owner of pyproject.toml
3 Re-check onnx-asr after its next release: if load_model(revision=...) ships, Parakeet becomes pinnable. Re-read stt/parakeet.py's "no offline switch" comment against that release watch #792 / #798
4 Test the Moonshine Hub redirect in an isolated HF_HOME (section 2, point 3) test (needs network, in a sandbox) maintainer
5 Record the snapshot commit and file digests per run in the #793 evaluation manifest protocol #793

Sources (all read 2026-11-06)