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Parakeet Multitalker Int8 Onnx

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KindOtherBase modelnvidia/multitalker-parakeet-streaming-0.6b-v1VersionRevision ab3add4

Model source

Kind
Other
File size
8.58 MB–1.16 GB
Base model
nvidia/multitalker-parakeet-streaming-0.6b-v1
Version
vRevision ab3add4
Updated
Sep 13, 2026
Downloads
0
Source
Hugging Face

Source description

Parakeet Multitalker (int8 ONNX) — Recogment mirror

Streaming joint ASR + 4-slot speaker diarization. This repo packages int8-quantized ONNX exports of the upstream NVIDIA NeMo checkpoint so that runtimes which don't depend on PyTorch / NeMo can use the model directly.

⚠️ Unofficial. This is a community-maintained mirror of derived artefacts. For the canonical model, citation, and training details see nvidia/multitalker-parakeet-streaming-0.6b-v1.

Files

FilePurposeSize
encoder.int8.onnxFastConformer encoder~626 MB
decoder_joint.int8.onnxRNN-T decoder + joint network~9 MB
tokenizer.modelSentencePiece tokenizer (1024 vocab)~245 KB

Provenance

These ONNX files were exported from the upstream NeMo .nemo checkpoint of nvidia/multitalker-parakeet-streaming-0.6b-v1 and then quantized to int8 for CPU inference. The conversion pipeline lives in the parakeet-rs project's tooling; the runtime that drives the resulting files is the same crate.

No model weights have been retrained, fine-tuned, or otherwise modified beyond the int8 quantization step.

Why this mirror exists

The Recogment daemon ships with a pinned set of model SHA-256 hashes and a zero-egress sandbox; the only outbound network in the whole product is a companion downloader binary that fetches from public HTTPS sources. Until this mirror existed, the Parakeet files had to be shipped to beta testers out-of-band as a tarball. With this mirror in place, the downloader can fetch them automatically alongside the rest of the public catalogue.

If you're not building Recogment, you almost certainly want the official NVIDIA repo linked above instead — it includes the original .nemo checkpoint, configuration, and reference NeMo inference code.

License

This work is licensed under the NVIDIA Open Model License. See NOTICE.txt in this repo for the required attribution notice, or read the full license text at the URL in the frontmatter above.

Permitted under that license: commercial use, redistribution (this repo), and derivative works (the int8 quantization). Required: include the NVIDIA Open Model License notice when you redistribute further.

Citation

Please cite the upstream model paper, not this mirror:

@misc{nvidia2024multitalkerparakeet,
  title={Multitalker Parakeet streaming 0.6B v1},
  author={NVIDIA},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/nvidia/multitalker-parakeet-streaming-0.6b-v1}}
}

Sources

1 source
Hugging FacePrimaryVersion ab3add4546b822854729251f301e1160e5fad663
huggingface.co/Recogment/parakeet-multitalker-int8-onnx/tree/ab3add4546b822854729251f301e1160e5fad663

Verified Sep 13

Model artifacts

5 artifacts

decoder_joint.int8.onnx

onnx · 8.58 MB · SHA-256 c18d0c0c31a7…8887 · Hugging Face

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encoder.int8.onnx

onnx · 627 MB · SHA-256 4372d298ec41…8cbd · Hugging Face

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static/decoder_joint.int8.onnx

onnx · 8.58 MB · SHA-256 f7abdc49aca9…9dc2 · Hugging Face

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static/encoder.fp16.onnx

onnx · 1.16 GB · SHA-256 b2a700b6342b…5228 · Hugging Face

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static/encoder.int8.onnx

onnx · 627 MB · SHA-256 ee338bcd8db3…fab6 · Hugging Face

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Source excerpts

2 excerpts

--- license: other license_name: nvidia-open-model-license license_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/ library_name: onnx pipeline_tag: automatic-speech-recognition language: - en tags: - automatic-speech-recognition - speaker-diarization - multitalker-asr - onnx - int8 - onnxruntime - parakeet - fastconformer - recogment base_model: nvidia/multitalker-parakeet-streaming-0.6b-v1 --- # Parakeet Multitalker (int8 ONNX) — Recogment mirror Streaming joint ASR + 4-slot speaker diarization. This repo packages **int8-quantized ONNX exports** of the upstream NVIDIA NeMo checkpoint so that runtimes which don't depend on PyTorch / NeMo can use the model directly. > ⚠️ **Unofficial.** This is a community-maintained mirror of derived artefacts. For the canonical model, citation, and training details see [nvidia/multitalker-parakeet-streaming-0.6b-v1](https://huggingface.co/nvidia/multitalker-parakeet-streaming-0.6b-v1). ## Files | File | Purpose | Size | |---|---|---| | `encoder.int8.onnx` | FastConformer encoder | ~626 MB | | `decoder_joint.int8.onnx` | RNN-T decoder + joint network | ~9 MB | | `tokenizer.model` | SentencePiece tokenizer (1024 vocab) | ~245 KB | ## Provenance These ONNX files were exported from the upstream NeMo `.nemo` checkpoint of [`nvidia/multitalker-parakeet-streaming-0.6b-v1`](https://huggingface.co/nvidia/multitalker-parakeet-streaming-0.6b-v1) and then quantized to int8 for CPU inference. The conversion pipeline lives in the [parakeet-rs](https://github.com/dnth/parakeet-rs) project's tooling; the runtime that drives the resulting files is the same crate. No model weights have been retrained, fine-tuned, or otherwise modified beyond the int8 quantization step. ## Why this mirror exists The [Recogment](https://github.com/kevin-atx/recogment) daemon ships with a pinned set of model SHA-256 hashes and a zero-egress sandbox; the only outbound network in the whole product is a companion downloader binary that fetches from public HTTPS sources. Until this mirror existed, the Parakeet files had to be shipped to beta testers out-of-band as a tarball. With this mirror in place, the downloader can fetch them automatically alongside the rest of the public catalogue. If you're not building Recogment, you almost certainly want the official NVIDIA repo linked above instead — it includes t...

Source context: 0 downloads · 1 likes · Pipeline automatic-speech-recognition · Library onnx · Repo Recogment/parakeet-multitalker-int8-onnx