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

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

upstream_commit: ef3bf40
pin_date: 2026-05-11

# 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: 12f1076
  date: 2026-05-11

# Upstream is the NVIDIA Open Model License (not a standard SPDX id), so
# the HF `license` field gets `other` and `license_name` / `license_link`
# carry the actual identifier + URL into the YAML frontmatter (HF prefers
# this when license=other). `license_display` is the human-facing form
# rendered in the README body.
license: other
license_name: nvidia-open-model-license
license_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
license_display: NVIDIA Open Model License
pipeline_tag: automatic-speech-recognition
languages:
  - en
tags:
  - gguf
  - transcribe.cpp
  - asr
  - speech-to-text
  - parakeet
  - conformer
  - rnnt
  - streaming
  - cache-aware

summary: |
  Offline English speech-to-text with punctuation and capitalization. A 0.6B-parameter cache-aware streaming FastConformer encoder with an RNN-T transducer decoder. Runs in offline mode. The encoder preserves the upstream att_context_size=[70, 13] (1.12s) cache-aware attention mask end-to-end. transcribe.cpp does not yet expose a streaming session API.

default_quant_index: 2  # Q8_0

# Capability flags for the transcribe_cpp metadata block.
capabilities:
  streaming: true
  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: 154.5
    cpu: 32
  ryzen-4750u:
    vulkan: 13
    cpu: 7.5

wer:
  source: LibriSpeech test-clean, offline
  notes: |
    WER measured on the full LibriSpeech test-clean split (2620 utterances) with greedy RNN-T decoding. F32 reference baseline: 2.31%. NVIDIA's self-reported number on the same split at att_context_size=[70, 13] (1.12s chunk, w/o PnC) is 2.32%.

quants:
  - name: F32
    filename: nemotron-speech-streaming-en-0.6b-F32.gguf
    size: 2.30 GB
    wer: 2.31%
  - name: F16
    filename: nemotron-speech-streaming-en-0.6b-F16.gguf
    size: 1.16 GB
    wer: 2.31%
  - name: Q8_0
    filename: nemotron-speech-streaming-en-0.6b-Q8_0.gguf
    size: 696 MB
    wer: 2.31%
  - name: Q6_K
    filename: nemotron-speech-streaming-en-0.6b-Q6_K.gguf
    size: 573 MB
    wer: 2.29%
  - name: Q5_K_M
    filename: nemotron-speech-streaming-en-0.6b-Q5_K_M.gguf
    size: 514 MB
    wer: 2.34%
  - name: Q4_K_M
    filename: nemotron-speech-streaming-en-0.6b-Q4_K_M.gguf
    size: 453 MB
    wer: 2.38%
