# Spec for the HF README of handy-computer/nemotron-3.5-asr-streaming-0.6b-gguf.
# Consumed by scripts/hf_cards/generate.py.

hf_repo: nvidia/nemotron-3.5-asr-streaming-0.6b
target_repo: handy-computer/nemotron-3.5-asr-streaming-0.6b-gguf
transcribe_docs_url: https://github.com/handy-computer/transcribe.cpp/blob/main/docs/models/nemotron-3.5-asr-streaming-0.6b.md

upstream_commit: 24b151a
pin_date: 2026-06-08

# 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: NeMo
  commit: 909e94e
  date: 2026-06-08

# Upstream is OpenMDW-1.1, not a standard SPDX id, so the HF `license`
# field gets `other` and `license_name` / `license_link` carry the actual
# identifier + URL. `license_display` is the human-facing form.
license: other
license_name: openmdw-1.1
license_link: https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b
license_display: OpenMDW-1.1
pipeline_tag: automatic-speech-recognition
languages:
  - en
  - es
  - fr
  - it
  - pt
  - nl
  - de
  - tr
  - ru
  - ar
  - hi
  - ja
  - ko
  - vi
  - uk
  - pl
  - sv
  - cs
  - nb
  - da
  - bg
  - fi
  - hr
  - sk
  - zh
  - hu
  - ro
  - et
tags:
  - gguf
  - transcribe.cpp
  - asr
  - speech-to-text
  - parakeet
  - conformer
  - rnnt
  - streaming
  - cache-aware
  - multilingual

summary: |
  Multilingual speech-to-text across 32 supported language-locales (the model's tokenizer recognizes 40, but 8 are adaptation-ready and need fine-tuning) with punctuation and capitalization. A 0.6B-parameter cache-aware streaming FastConformer encoder with a prompt-conditioned RNN-T transducer decoder; the target language is selected per call (--language en-US, fr-FR, de-DE, ...) and an auto mode emits a <lang-XX> tag. Ships both the offline path (att_context_size=[56, 13], 1.12s, headline accuracy) and runtime-selectable chunked streaming (--stream-chunk-ms 1120 --stream-att-right {0,3,6,13}).

default_quant_index: 2  # Q8_0

# Capability flags for the transcribe_cpp metadata block.
capabilities:
  streaming: true
  translate: false
  lang_detect: true
  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: 98
    cpu: 29
  ryzen-4750u:
    vulkan: 14.5
    cpu: 7.5

wer:
  metadata_key: fleurs_en
  source: FLEURS test en (en-US), offline att_context_size=[56, 13]
  notes: |
    WER measured on FLEURS test en (647 utterances), greedy RNN-T, --language en-US, whisper-normalizer scoring; the per-quant column is FLEURS en. NeMo reference baseline on the same manifest: 7.99% (NVIDIA self-reports 7.91% en-US). On LibriSpeech test-clean (2620 utterances) the same presets score F32 3.04 / F16 3.03 / Q8_0 3.06 / Q6_K 3.07 / Q5_K_M 3.10 / Q4_K_M 3.28, against a 3.03% NeMo reference.
  librispeech_test_clean:
    f32: 3.04
    f16: 3.03
    q8_0: 3.06
    q6_k: 3.07
    q5_k_m: 3.10
    q4_k_m: 3.28

quants:
  - name: F32
    filename: nemotron-3.5-asr-streaming-0.6b-F32.gguf
    size: 2.38 GB
    wer: 7.97%
  - name: F16
    filename: nemotron-3.5-asr-streaming-0.6b-F16.gguf
    size: 1.19 GB
    wer: 7.97%
  - name: Q8_0
    filename: nemotron-3.5-asr-streaming-0.6b-Q8_0.gguf
    size: 716 MB
    wer: 7.88%
  - name: Q6_K
    filename: nemotron-3.5-asr-streaming-0.6b-Q6_K.gguf
    size: 593 MB
    wer: 8.02%
  - name: Q5_K_M
    filename: nemotron-3.5-asr-streaming-0.6b-Q5_K_M.gguf
    size: 534 MB
    wer: 8.15%
  - name: Q4_K_M
    filename: nemotron-3.5-asr-streaming-0.6b-Q4_K_M.gguf
    size: 473 MB
    wer: 8.49%
