| Phonon-2 |
| Copyright 2026 Fermion Research |
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| This product includes software and models developed by Fermion Research. |
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| BASE MODEL |
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| This model is derived from NVIDIA's Parakeet TDT 0.6B v3 |
| (nvidia/parakeet-tdt-0.6b-v3), (c) NVIDIA Corporation, licensed under the |
| Creative Commons Attribution 4.0 International licence (CC-BY-4.0). |
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| https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3 |
| https://creativecommons.org/licenses/by/4.0/ |
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| Changes: the encoder's linear weights were re-trained and quantised to a |
| five-value alphabet by Fermion Research; the remaining parameters were |
| quantised to 6-bit integer tables. The FastConformer encoder architecture, |
| the TDT decoder, the tokenizer and the feature-extractor configuration derive |
| from that model and remain under CC-BY-4.0. |
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| These weights are therefore distributed under CC-BY-4.0. The Fermion code in |
| this repository remains under the Apache License, Version 2.0. |
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| TRAINING DATA |
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| Training audio includes CHiME-6, distributed under the Creative Commons |
| Attribution-ShareAlike 4.0 International licence (CC-BY-SA-4.0) |
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| https://chimechallenge.github.io/chime6/ |
| https://creativecommons.org/licenses/by-sa/4.0/ |
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| and SPGISpeech, used under Kensho's public terms |
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| https://datasets.kensho.com/datasets/spgispeech |
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| RUNTIME DEPENDENCIES |
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| MLX ......................... MIT License ......... https://github.com/ml-explore/mlx |
| mlx-audio ................... MIT License ......... https://github.com/Blaizzy/mlx-audio |
| The Parakeet model graph (feature extraction, FastConformer encoder, |
| TDT decoder and greedy search) is mlx-audio's implementation. |
| NumPy ....................... BSD-3-Clause ........ https://numpy.org |
| soundfile ................... BSD-3-Clause ........ https://github.com/bastibe/python-soundfile |
| soundfile links libsndfile (LGPL-2.1), dynamically and unmodified, as |
| distributed in the standard soundfile wheel. |
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| REFERENCE RUNTIME (optional) |
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| PyTorch ..................... BSD-3-Clause ........ https://pytorch.org |
| transformers ................ Apache-2.0 .......... https://github.com/huggingface/transformers |
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