Views
No views yet
nb-whisper-small/
├── MelSpectrogram.mlmodelc 372 KB
├── AudioEncoder.mlmodelc 170 MB
├── TextDecoder.mlmodelc 293 MB
├── config.json
└── generation_config.jsonargmaxinc/whisperkit-coreml, which is
what WhisperKitConfig(model:modelRepo:) expects to find.parrot --bilingual1let config = WhisperKitConfig(
2 model: "nb-whisper-small",
3 modelRepo: "Barrymanalow/nb-whisper-coreml"
4)
5let pipe = try await WhisperKit(config)scripts/convert-nb-whisper.sh
in the papegøye repo. Two things that trip up a naive run, both handled by that
script:whisperkittools pins torch==2.5.0, which has no wheels above CPython 3.12.
On a Mac defaulting to a newer Python, pip install fails with a bare "no
matching distribution" that never mentions the version.whisperkit-generate-model emits only the compiled .mlmodelc bundles.
config.json and generation_config.json stay behind in the source snapshot
and have to be copied across, or WhisperKit has no config to read.scripts/convert-nb-whisper.sh smallvocab_size 51865). Practical consequences:<|no|> token onto English audio does not fail loudly — it
renders the English speech as fluent Norwegian, which reads like a correct
translation. Anything routing audio to this model should be confident the
audio really is Norwegian. See
papegøye#22.powermetrics, and a
systematic word-level diff against the PyTorch checkpoint. The CoreML compute
plan targets ANE for nearly every operation, but that is the plan, not a
measurement.