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cstr/parakeet-rnnt-1.1b-GGUF overview

parakeet rnnt 1.1b — GGUF GGUF conversions of nvidia/parakeet rnnt 1.1b https://huggingface.co/nvidia/parakeet rnnt 1.1b for use with CrispASR https://github.c…

ggufasrspeechrnntenbase_model:nvidia/parakeet-rnnt-1.1bbase_model:quantized:nvidia/parakeet-rnnt-1.1blicense:cc-by-4.0region:us

Runs locally from ~652.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

2 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
parakeet-rnnt-1.1b-f16.ggufGGUFF162.00 GBDownload
parakeet-rnnt-1.1b-q4_k.ggufGGUFQ4_K652.0 MBDownload

Model Details

Model IDcstr/parakeet-rnnt-1.1b-GGUF
Authorcstr
Pipeline
Licensecc-by-4.0
Base modelnvidia/parakeet-rnnt-1.1b
Last modified2026-08-02T15:35:19.000Z

Model README

---

license: cc-by-4.0

language:

- en

tags:

- asr

- speech

- gguf

- rnnt

base_model: nvidia/parakeet-rnnt-1.1b

---

parakeet-rnnt-1.1b — GGUF

GGUF conversions of nvidia/parakeet-rnnt-1.1b for use with CrispASR.

Files

| File | Size | Quantization |

|------|------|-------------|

| parakeet-rnnt-1.1b-q4_k.gguf | ~770 MB | Q4_K (recommended) |

| parakeet-rnnt-1.1b-f16.gguf | ~2.1 GB | F16 (full precision) |

Usage

crispasr --backend parakeet \
  -m parakeet-rnnt-1.1b-q4_k.gguf \
  -f audio.wav

Or let CrispASR auto-download:

crispasr --backend parakeet-rnnt-1.1b -f audio.wav

Architecture

  • Model: standard RNN-Transducer (no TDT duration head)
  • Encoder: 42-layer FastConformer, 80-mel input, d_model=1024
  • Decoder: RNN predictor + joint network
  • Vocab: 1024-token BPE (lowercase English)
  • Sample rate: 16 kHz

The RNNT decoder is auto-detected at runtime via n_tdt_durations==0.

License

nvidia/parakeet-rnnt-1.1b is released under the CC BY 4.0 license.

Provenance and EU AI Act Art. 53 note

  • Upstream model: nvidia/parakeet-rnnt-1.1b — 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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