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handy-computer/moonshine-base-ar-gguf

🤗 Hugging Face 来源automatic-speech-recognitionmit914 MBGGUF✓ 3 个校验和今天更新
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moonshine-base-ar: transcribe.cpp GGUF

GGUF conversions of UsefulSensors/moonshine-base-ar for use with transcribe.cpp.

Ported from upstream commit 264cc18, pinned 2026-05-12. Validated against the transformers reference at transcribe.cpp commit 90bf720 on 2026-05-12.

UsefulSensors' Moonshine base fine-tuned on Arabic. Same encoder-decoder transformer architecture as moonshine-base (62M parameters): consumes 16 kHz raw PCM via a three-layer Conv1d stem (no STFT, no mel filterbank) and emits transcript-only output. Single-language (ar); no translation, no language detection, no timestamps.

Downloads

Quantization Download Size WER (FLEURS ar test)
F32 moonshine-base-ar-F32.gguf 248 MB 24.45%
F16 moonshine-base-ar-F16.gguf 132 MB 24.45%
Q8_0 moonshine-base-ar-Q8_0.gguf 77 MB 24.50%

WER on the full FLEURS ar split (428 utterances), batch size 1, timestamps none. Figures without a commit were published before provenance was recorded.

Decoded with the transcribe.cpp defaults (greedy, num_beams=1, max_length=192, matching the upstream generation_config).

UsefulSensors does not publish a per-language WER number for this variant. As a comparable baseline we ran the Transformers F32 reference (MoonshineForConditionalGeneration, fp32 on MPS) on the same manifest: 24.51% WER. The C++ F32/F16 numbers above match the reference within bootstrap-CI noise; Q8_0 introduces a small additional drift from F16 (typically within 0.1pp).

Usage

Build transcribe.cpp from source:

git clone git@github.com:handy-computer/transcribe.cpp.git
cd transcribe.cpp
cmake -B build && cmake --build build

Run on a 16 kHz mono WAV:

build/bin/transcribe-cli \
  -m moonshine-base-ar-Q8_0.gguf \
  input.wav

If your audio isn't already 16 kHz mono WAV, convert it first:

ffmpeg -i input.mp3 -ar 16000 -ac 1 output.wav

See the transcribe.cpp model page for performance numbers, numerical validation, and reproduction steps.

License

Inherited from the base model: MIT. See the upstream model card for full terms.

Original Model Card

The section below is reproduced from UsefulSensors/moonshine-base-ar at commit 264cc18 for offline reference. The upstream card is the authoritative source.

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