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Stt En Fastconformer Ctc Large GGUF

GGUF quantisations of nvidia/sttenfastconformerctclarge for CrispASR.

KindOtherBase modelnvidia/stt_en_fastconformer_ctc_largeVersionRevision 2eb7779Bgrade

Model source

Kind
Other
File size
70.3–221 MB
Base model
nvidia/stt_en_fastconformer_ctc_large
Version
vRevision 2eb7779
Updated
Sep 26, 2026
Downloads
968
Source
Hugging Face

Source description

stt-en-fastconformer-ctc-large-GGUF

GGUF quantisations of nvidia/stt_en_fastconformer_ctc_large for CrispASR.

QuantSizeDescription
F16222 MBFull precision
Q8_0132 MB8-bit
Q5_095 MB5-bit
Q4_K83 MB4-bit K-quant (recommended)

Architecture

18-layer NeMo FastConformer encoder + Conv1d CTC head. d_model=512, 8 heads, 1024 SentencePiece vocab, English only, 80 log-mel features, ~115M params.

Usage

crispasr --backend fastconformer-ctc -m stt-en-fastconformer-ctc-large-q4_k.gguf -f audio.wav

NeMo Family

Same --backend fastconformer-ctc supports large (18L/512d), xlarge (24L/1024d), and xxlarge (42L/1024d).

Provenance and EU AI Act Art. 53 note

  • Upstream model: nvidia/stt_en_fastconformer_ctc_large — published by nvidia.
  • Upstream licence: cc-by-4.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
  • What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
  • Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
  • Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.

Sources

1 source
Hugging FacePrimaryVersion 2eb77792d5831888acc530ee78c0a245b101aa21
huggingface.co/cstr/stt-en-fastconformer-ctc-large-GGUF/tree/2eb77792d5831888acc530ee78c0a245b101aa21

Verified Sep 6

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Model artifacts

4 artifacts

stt-en-fastconformer-ctc-large-f16.gguf

gguf · 221 MB · SHA-256 78dd76f13798…30f8 · Hugging Face

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stt-en-fastconformer-ctc-large-q4_k.gguf

gguf · 70.3 MB · SHA-256 834c5e6e85eb…a467 · Hugging Face

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stt-en-fastconformer-ctc-large-q5_0.gguf

gguf · 82.3 MB · SHA-256 2be16a739a9e…e8f3 · Hugging Face

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stt-en-fastconformer-ctc-large-q8_0.gguf

gguf · 118 MB · SHA-256 d56c6a5fcae8…fdd7 · Hugging Face

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Source excerpts

2 excerpts

--- license: cc-by-4.0 base_model: nvidia/stt_en_fastconformer_ctc_large language: - en tags: - automatic-speech-recognition - gguf - crispasr - fastconformer - ctc - nemo pipeline_tag: automatic-speech-recognition --- # stt-en-fastconformer-ctc-large-GGUF GGUF quantisations of [nvidia/stt_en_fastconformer_ctc_large](https://huggingface.co/nvidia/stt_en_fastconformer_ctc_large) for [CrispASR](https://github.com/CrispStrobe/CrispASR). | Quant | Size | Description | |---|---|---| | F16 | 222 MB | Full precision | | Q8_0 | 132 MB | 8-bit | | Q5_0 | 95 MB | 5-bit | | Q4_K | 83 MB | 4-bit K-quant (recommended) | ## Architecture 18-layer NeMo FastConformer encoder + Conv1d CTC head. d_model=512, 8 heads, 1024 SentencePiece vocab, English only, 80 log-mel features, ~115M params. ## Usage ```bash crispasr --backend fastconformer-ctc -m stt-en-fastconformer-ctc-large-q4_k.gguf -f audio.wav ``` ## NeMo Family Same `--backend fastconformer-ctc` supports large (18L/512d), xlarge (24L/1024d), and xxlarge (42L/1024d). ## Provenance and EU AI Act Art. 53 note - **Upstream model:** [nvidia/stt_en_fastconformer_ctc_large](https://huggingface.co/nvidia/stt_en_fastconformer_ctc_large) — published by `nvidia`. - **Upstream licence:** `cc-by-4.0`. This repository redistributes under the same terms; it grants no rights the upstream licence does not. - **What was done here:** format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs. - **Training data:** documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository. - **Provider status:** under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.

Source context: 968 downloads · 0 likes · Pipeline automatic-speech-recognition · Library nemo · Repo cstr/stt-en-fastconformer-ctc-large-GGUF