# Spec for the HF README of handy-computer/gigaam-v3-e2e-rnnt-gguf.
# Consumed by scripts/hf_cards/generate.py.

hf_repo: ai-sage/GigaAM-v3
target_repo: handy-computer/gigaam-v3-e2e-rnnt-gguf
transcribe_docs_url: https://github.com/handy-computer/transcribe.cpp/blob/main/docs/models/gigaam-v3-e2e-rnnt.md

# Upstream branch: main (= v3_e2e_rnnt). Each gigaam-v3 variant lives on its own
# HF branch; the SHA below pins this variant's branch revision.
upstream_commit: ec1dc1f
pin_date: 2026-05-12
# Upstream README lives only on the main branch; this variant IS main, so
# upstream_card_commit matches upstream_commit. Made explicit for symmetry
# with the sibling YAMLs that override it to ec1dc1f.
upstream_card_commit: ec1dc1f

# Validation pin for the most recent upload. Updated on each release;
# older HF revisions carry whatever value was current at their upload time.
validation:
  reference: gigaam author package
  commit: 42b96d9
  date: 2026-05-12

license: mit
license_display: MIT
pipeline_tag: automatic-speech-recognition
languages:
  - ru
tags:
  - gguf
  - transcribe.cpp
  - asr
  - speech-to-text
  - gigaam
  - conformer
  - rnnt
  - russian

summary: |
  Offline Russian speech-to-text with greedy RNN-T decoding. 16-layer Conformer encoder paired with an RNN-T transducer head. Output is cased Russian with punctuation, decoded from a 1024-piece SentencePiece tokenizer. Not a streaming model and does not translate. Short-form only (≤25 s per utterance).

default_quant_index: 2  # Q8_0

# Capability flags for the transcribe_cpp metadata block.
capabilities:
  streaming: false
  translate: false
  lang_detect: false
  timestamps: token  # 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: 88
    cpu: 25
  ryzen-4750u:
    vulkan: 22
    cpu: 8

wer:
  metadata_key: fleurs_ru
  source: FLEURS ru
  notes: |
    WER measured on the full FLEURS ru test split (775 utterances) with greedy decoding and no external LM. F32 reference baseline: 5.35%. Upstream `gigaam` author package measured on the same manifest: 6.78%; the 1.4 pp gap is upstream rejecting 5 long (>25 s) utterances with `Too long wav file, use 'transcribe_longform' method.` (counted as 100% deletion errors). On the 770-utt subset both sides decode, transcribe.cpp matches upstream exactly. ai-sage does not publish a FLEURS ru WER; this number is measured here.

quants:
  - name: F32
    filename: gigaam-v3-e2e-rnnt-F32.gguf
    size: 849 MB
    wer: 5.35%
  - name: F16
    filename: gigaam-v3-e2e-rnnt-F16.gguf
    size: 431 MB
    wer: 5.35%
  - name: Q8_0
    filename: gigaam-v3-e2e-rnnt-Q8_0.gguf
    size: 261 MB
    wer: 5.36%
  - name: Q6_K
    filename: gigaam-v3-e2e-rnnt-Q6_K.gguf
    size: 217 MB
    wer: 5.37%
  - name: Q5_K_M
    filename: gigaam-v3-e2e-rnnt-Q5_K_M.gguf
    size: 197 MB
    wer: 5.42%
  - name: Q4_K_M
    filename: gigaam-v3-e2e-rnnt-Q4_K_M.gguf
    size: 175 MB
    wer: 5.36%
