# Spec for the HF README of handy-computer/moonshine-base-gguf.
# Consumed by scripts/hf_cards/generate.py.

hf_repo: UsefulSensors/moonshine-base
target_repo: handy-computer/moonshine-base-gguf
transcribe_docs_url: https://github.com/handy-computer/transcribe.cpp/blob/main/docs/models/moonshine-base.md

upstream_commit: 7a73d8d
pin_date: 2026-05-05

validation:
  reference: transformers
  commit: 07a8a84
  date: 2026-05-05

license: mit
license_display: MIT
pipeline_tag: automatic-speech-recognition
languages:
  - en
tags:
  - gguf
  - transcribe.cpp
  - asr
  - speech-to-text
  - moonshine
  - useful-sensors
  - encoder-decoder

summary: |
  Useful Sensors Moonshine base — a 61M-parameter encoder-decoder transformer
  for English speech recognition. Consumes raw 16 kHz PCM directly via a
  three-layer Conv1d stem (no STFT, no mel) and emits transcript-only output.
  Wider and deeper than moonshine-tiny (8 encoder / 8 decoder layers, hidden
  size 416, partial RoPE 0.62). English-only; no translation, no language
  detection, no timestamps.

default_quant_index: 2  # Q8_0

# Capability flags for the transcribe_cpp metadata block.
capabilities:
  streaming: false
  translate: false
  lang_detect: false
  timestamps: none  # none | segment | word | token

# Speedup-over-realtime (×RT) per rig/backend, from docs/models; published
# raw as rtf_<machine> in the metadata block.
perf:
  m4-max:
    metal: 79.5
    cpu: 80.5
  ryzen-4750u:
    vulkan: 34.5
    cpu: 22

wer:
  source: LibriSpeech test-clean
  notes: |
    WER measured on the full LibriSpeech test-clean split (2620 utterances)
    with the transcribe.cpp default decode (greedy, num_beams=1,
    max_length=194 — matching the upstream generation_config). Upstream
    reports 3.27% on the same split (Moonshine paper, Table 2; also Open
    ASR Leaderboard). Our F32 reference baseline lands at 3.28%, identical
    to upstream within rounding and well within the ±1.00 pp Stage 7
    acceptance gate. Q8_0 lands at 3.26%, slightly under F32 — that delta
    sits inside the 95% bootstrap CI and is noise, not a real improvement.

quants:
  - name: F32
    filename: moonshine-base-F32.gguf
    size: 236 MB
    wer: 3.28%
  - name: F16
    filename: moonshine-base-F16.gguf
    size: 126 MB
    wer: 3.28%
  - name: Q8_0
    filename: moonshine-base-Q8_0.gguf
    size: 74 MB
    wer: 3.26%
