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cstr/stt-en-fastconformer-ctc-xlarge-GGUF overview

stt en fastconformer ctc xlarge GGUF GGUF quantisations of nvidia/stt en fastconformer ctc xlarge https://huggingface.co/nvidia/stt en fastconformer ctc xlarge…

ggufautomatic-speech-recognitioncrispasrenbase_model:nvidia/stt_en_fastconformer_ctc_xlargebase_model:quantized:nvidia/stt_en_fastconformer_ctc_xlargelicense:cc-by-4.0region:us

Runs locally from ~366.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
191
Likes
1
Pipeline
automatic-speech-recognition
Author

Repository Files & Downloads

4 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
stt-en-fastconformer-ctc-xlarge-f16.ggufGGUFF161.14 GBDownload
stt-en-fastconformer-ctc-xlarge-q4_k.ggufGGUFQ4_K366.0 MBDownload
stt-en-fastconformer-ctc-xlarge-q5_0.ggufGGUFQ5_0429.4 MBDownload
stt-en-fastconformer-ctc-xlarge-q8_0.ggufGGUFQ8_0619.8 MBDownload

Model Details

Model IDcstr/stt-en-fastconformer-ctc-xlarge-GGUF
Authorcstr
Pipelineautomatic-speech-recognition
Licensecc-by-4.0
Base modelnvidia/stt_en_fastconformer_ctc_xlarge
Last modified2026-08-02T15:40:35.000Z

Model README

---

license: cc-by-4.0

base_model: nvidia/stt_en_fastconformer_ctc_xlarge

language:

- en

tags:

- automatic-speech-recognition

- gguf

- crispasr

pipeline_tag: automatic-speech-recognition

---

stt-en-fastconformer-ctc-xlarge-GGUF

GGUF quantisations of nvidia/stt_en_fastconformer_ctc_xlarge for CrispASR.

| Quant | Description |

|---|---|

| F16 | Full precision |

| Q8_0 | 8-bit |

| Q5_0 | 5-bit |

| Q4_K | 4-bit K-quant (recommended) |

Usage

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

Provenance and EU AI Act Art. 53 note

  • Upstream model: nvidia/stt_en_fastconformer_ctc_xlarge — 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.

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