---
license: mit
base_model: UsefulSensors/moonshine-base-uk
base_model_relation: quantized
library_name: transcribe.cpp
pipeline_tag: automatic-speech-recognition
language:
  - uk
tags:
  - gguf
  - transcribe.cpp
  - asr
  - speech-to-text
  - moonshine
  - useful-sensors
  - encoder-decoder
transcribe_cpp:
  wer_fleurs_uk:
    f32: 14.49
    f16: 14.49
    q8_0: 14.39
  rtf_m4_max:
    metal: 79.5
    cpu: 80.5
  rtf_ryzen_4750u:
    vulkan: 34.5
    cpu: 22
  streaming: false
  translate: false
  lang_detect: false
  timestamps: none
---

# moonshine-base-uk: transcribe.cpp GGUF

GGUF conversions of [UsefulSensors/moonshine-base-uk](https://huggingface.co/UsefulSensors/moonshine-base-uk) for use
with [transcribe.cpp](https://github.com/handy-computer/transcribe.cpp).

Ported from upstream commit
[a52b2e9](https://huggingface.co/UsefulSensors/moonshine-base-uk/commit/a52b2e9),
pinned 2026-05-12.
Validated against the transformers reference at transcribe.cpp commit
[90bf720](https://github.com/handy-computer/transcribe.cpp/tree/90bf720)
on 2026-05-12.

UsefulSensors' Moonshine base fine-tuned on Ukrainian. 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
(uk); no translation, no language detection, no timestamps.


## Downloads

| Quantization | Download | Size | WER (FLEURS uk test) |
| --- | --- | ---: | ---: |
| F32 | [moonshine-base-uk-F32.gguf](https://huggingface.co/handy-computer/moonshine-base-uk-gguf/resolve/main/moonshine-base-uk-F32.gguf) | 236 MB | 14.49% |
| F16 | [moonshine-base-uk-F16.gguf](https://huggingface.co/handy-computer/moonshine-base-uk-gguf/resolve/main/moonshine-base-uk-F16.gguf) | 126 MB | 14.49% |
| Q8_0 | [moonshine-base-uk-Q8_0.gguf](https://huggingface.co/handy-computer/moonshine-base-uk-gguf/resolve/main/moonshine-base-uk-Q8_0.gguf) | 74 MB | 14.39% |

WER measured on the FLEURS-uk test split (750
utterances) using the transcribe.cpp default decode (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: **14.51% 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:

```bash
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:

```bash
build/bin/transcribe-cli \
  -m moonshine-base-uk-Q8_0.gguf \
  input.wav
```

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

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

See the [transcribe.cpp model page](https://github.com/handy-computer/transcribe.cpp/blob/main/docs/models/moonshine.md) for performance
numbers, numerical validation, and reproduction steps.

## License

Inherited from the base model: **MIT**. See the
[upstream model card](https://huggingface.co/UsefulSensors/moonshine-base-uk) for full terms.

---

## Original Model Card

> The section below is reproduced from
> [UsefulSensors/moonshine-base-uk](https://huggingface.co/UsefulSensors/moonshine-base-uk) at commit
> `a52b2e9` for offline reference. The upstream card is the
> authoritative source.

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