# Spec for the HF README of handy-computer/canary-1b-v2-gguf.
# Consumed by scripts/hf_cards/generate.py.

hf_repo: nvidia/canary-1b-v2
target_repo: handy-computer/canary-1b-v2-gguf
transcribe_docs_url: https://github.com/handy-computer/transcribe.cpp/blob/main/docs/models/canary-1b-v2.md

upstream_commit: 87bc526
pin_date: 2026-05-08

validation:
  reference: NeMo
  commit: db53eda
  date: 2026-05-08

license: cc-by-4.0
license_display: CC-BY-4.0
pipeline_tag: automatic-speech-recognition
languages:
  - bg
  - hr
  - cs
  - da
  - nl
  - en
  - et
  - fi
  - fr
  - de
  - el
  - hu
  - it
  - lv
  - lt
  - mt
  - pl
  - pt
  - ro
  - sk
  - sl
  - es
  - sv
  - ru
  - uk
tags:
  - gguf
  - transcribe.cpp
  - asr
  - speech-to-text
  - canary
  - multitask-aed
  - encoder-decoder
  - multilingual
  - translation

summary: |
  Offline multilingual speech-to-text and translation across 25 European
  languages. A 978M-parameter multitask AED with a 32-layer FastConformer
  encoder and an 8-layer Transformer decoder. Supports automatic speech
  recognition for any of the 25 supported languages, plus translation
  between supported language pairs (per the upstream model card). Takes
  a 16 kHz mono WAV and produces a transcript. Not a streaming model;
  word and segment timestamps from the upstream model are not exposed in
  the v1 port.

default_quant_index: 2  # Q8_0

# Capability flags for the transcribe_cpp metadata block.
capabilities:
  streaming: false
  translate: true
  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: 85.2
    cpu: 18.9
  ryzen-4750u:
    vulkan: 13.2
    cpu: 6.7

wer:
  source: LibriSpeech test-clean
  notes: |
    WER measured on the full LibriSpeech test-clean split (2620 utterances)
    with greedy decoding and no external LM. F32 reference baseline: 1.92%.
    NVIDIA's self-reported number on the upstream model card is 2.18%;
    our F32 port comes in slightly under the upstream-reported number
    (Δ −0.26pp) and is likely down to scoring differences.

quants:
  - name: F32
    filename: canary-1b-v2-F32.gguf
    size: 3.7 GB
    wer: 1.92%
  - name: F16
    filename: canary-1b-v2-F16.gguf
    size: 1.8 GB
    wer: 1.92%
  - name: Q8_0
    filename: canary-1b-v2-Q8_0.gguf
    size: 1.1 GB
    wer: 1.91%
  - name: Q6_K
    filename: canary-1b-v2-Q6_K.gguf
    size: 889 MB
    wer: 1.94%
  - name: Q5_K_M
    filename: canary-1b-v2-Q5_K_M.gguf
    size: 798 MB
    wer: 1.93%
  - name: Q4_K_M
    filename: canary-1b-v2-Q4_K_M.gguf
    size: 701 MB
    wer: 1.91%
