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Rekody/rekody-streaming-en-0.6b-int8
rekody-streaming-en-0.6b-int8 is a automatic speech recognition model from Rekody. Use it when you need speech turned into text. The card lists the license as other.
An int8 ONNX conversion of NVIDIA's Nemotron speech streaming 0.6B model (the March 2026 checkpoint), packaged for on-device streaming dictation. This is the model behind Rekody, the private, local-first voice dictati…
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From the Hugging Face model README
An int8 ONNX conversion of NVIDIA's Nemotron speech streaming 0.6B model (the March 2026 checkpoint), packaged for on-device streaming dictation. This is the model behind Rekody, the private, local-first voice dictation tool for macOS.
encoder.onnx (int8, 880 MB), decoder_joint.onnx (int8,
11 MB), tokenizer.model (SentencePiece), and config.json.Word error rate (WER, %), lower is better. Measured with the Open ASR
Leaderboard methodology (hf-audio/open-asr-leaderboard @ b6bdcd0b,
EnglishTextNormalizer), on identical audio and with the identical
normalizer for both models.
| Dataset | rekody-streaming-en-0.6b-int8 | openai/whisper-large-v3-turbo |
|---|---|---|
| AMI | 12.36 | 13.86 |
| Earnings22 | 12.27 | 10.81 |
| Gigaspeech | 8.64 | 8.34 |
| LibriSpeech test-clean | 2.09 | 1.60 |
| LibriSpeech test-other | 4.92 | 3.75 |
| SPGISpeech | 2.99 | 2.78 |
| Voxpopuli | 2.74 | 5.31 |
| Average | 6.57 | 6.64 |
Note the operating points: this model streams, producing text as audio arrives in 560 ms chunks, while whisper-large-v3-turbo is a batch model that sees each full recording before emitting anything. Matching a strong batch model's average WER under a streaming constraint is the point of this model.
Two licenses apply to this repository, and users must comply with both:
LICENSE). PolyForm Shield is a noncompete license: any use is
permitted except providing a product that competes with the software or
with the licensor's products built on it.NOTICE and the dated copy in licenses/).| File | SHA-256 |
|---|---|
encoder.onnx | 83538392358e90c40592f7cf99ee65ac7dca5d144edb999ce028c372318a5753 |
decoder_joint.onnx | 89cae615623e41e94cc6b428708cd1a89a22965606fe7ded814b1d8e20c87368 |
tokenizer.model | 07d4e5a63840a53ab2d4d106d2874768143fb3fbdd47938b3910d2da05bfb0a9 |
config.json | 19c6a445ddf0268a8ab3653f0cdf5740196271ba0a902eaae8d17de52f74a829 |
These hashes are also published in SHA256SUMS.
df1f0fe9dfdf05152936192b4c8c7653d53bf557 (the March 13, 2026
checkpoint).quantize_dynamic QInt8 over MatMul and LSTM ops.Contact: [email protected]