moonshine-tiny-de-dattazigzag-GGUF – AI Model by cstr | AlphaNeural AI

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cstr/
moonshine-tiny-de-dattazigzag-GGUF

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speech-recognition

automatic-speech-recognition

dattazigzag/moonshine-tiny-de

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Moonshine Tiny (German, dattazigzag) -- GGUF

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

Available variants

File	Quant	Size	Notes
`moonshine-tiny-de-dattazigzag-f16.gguf`	F16	52 MB	Half precision
`moonshine-tiny-de-dattazigzag-q4_k.gguf`	Q4_K	17 MB	Best size/quality tradeoff

Model details

Architecture: Conv1d stem + 6L transformer encoder + 6L transformer decoder (288d, 8 heads, partial RoPE, SiLU/GELU)
Parameters: 27M
Languages: German (fine-tuned from English moonshine-tiny)
WER: 36.7% on MLS German test set
Training data: MLS German (~1,967 hours), 10k steps
Output: Lowercase only, no punctuation
License: MIT (inherited from upstream)
Source: dattazigzag/moonshine-tiny-de

Usage with CrispASR

bash

# Explicit model path
./build/bin/crispasr --backend moonshine -m moonshine-tiny-de-dattazigzag-q4_k.gguf -f audio.wav

Notes

Moonshine models run on CPU only (GPU not needed for these small models)
Tokenizer (tokenizer.bin) must be in the same directory as the model file
For better German quality, consider moonshine-base-de-fidoriel (6.9% WER) or moonshine-tiny-de-fidoriel (11.4% WER)