Moonshine Tiny -- GGUF

GGUF conversions and quantisations of UsefulSensors/moonshine-tiny for use with CrispStrobe/CrispASR.

Available variants

File Quant Size Notes
moonshine-tiny.gguf F32 104 MB Full precision
moonshine-tiny-q8_0.gguf Q8_0 33 MB High quality
moonshine-tiny-q4_k.gguf Q4_K 21 MB Best size/quality tradeoff

All variants produce correct transcription on test audio.

Model details

  • Architecture: Conv1d stem + 6L transformer encoder + 6L transformer decoder (288d, 8 heads, partial RoPE, SiLU/GELU)
  • Parameters: 27M
  • Languages: English only
  • WER: 4.55% (LibriSpeech clean), 11.68% (Other)
  • Performance: 11.2x realtime on CPU (F32)
  • License: MIT
  • Source: moonshine.cpp (MIT)

Usage with CrispASR

./build/bin/crispasr -m moonshine-tiny-q4_k.gguf -f audio.wav
./build/bin/crispasr --backend moonshine -m moonshine-tiny-q4_k.gguf -f audio.wav -osrt

Provenance and EU AI Act Art. 53 note

  • Upstream model: UsefulSensors/moonshine-tiny โ€” published by UsefulSensors.
  • Upstream licence: mit. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
  • What was done here: format conversion and/or quantisation only (GGUF/GGML). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
  • Training data: documented โ€” where it is documented at all โ€” by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
  • Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.
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