Instructions to use FermionResearch/Phonon-2.5-English with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use FermionResearch/Phonon-2.5-English with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download FermionResearch/Phonon-2.5-English --local-dir Phonon-2.5-English
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Phonon-2.5 English
Phonon-2.5 English is an open speech recognition model for English in a 157.6 MB download. Across the Open ASR Leaderboard's seven English sets it averages 4.82 % word error, against 4.94 % for Underdog Bark 3.0, the other low-bit model of this size, and 5.21 % for Phonon-2. It is better than Phonon-2 on all seven sets. The same file runs on Apple silicon and on Linux and Windows CPUs, with no GPU needed.
Why a separate English model? Some workloads want English text and nothing else: dictation, captions, compliance and search pipelines built around English. Phonon-2.5 English is for those, and it is our most accurate English model.
For 25 languages, see Phonon-2.5, the same size.
Benchmarks
Word error rate, %, lower is better; the best value in each column is in bold.
| Model | Download | LS clean | LS other | AMI | Earnings-22 | GigaSpeech | SPGISpeech | VoxPopuli | Average |
|---|---|---|---|---|---|---|---|---|---|
| Phonon-2.5 English | 157.6 MB | 1.64 | 3.56 | 8.76 | 6.22 | 7.99 | 3.31 | 2.28 | 4.82 |
| Phonon-2.5 (25 languages) | 156.2 MB | 1.60 | 3.41 | 9.12 | 6.72 | 8.04 | 3.31 | 3.23 | 5.06 |
| Phonon-2 | 158 MB | 1.72 | 3.92 | 9.37 | 6.96 | 8.35 | 3.70 | 2.46 | 5.21 |
| Underdog Bark 3.0 | 163 MB | 1.89 | 4.08 | 7.82 | 7.05 | 7.95 | 3.72 | 2.05 | 4.94 |
| Parakeet TDT 0.6B v3โ | 2,508 MB | 1.52 | 3.13 | 9.42 | 5.85 | 7.99 | 3.63 | 3.19 | 4.96 |
| Parakeet Redux | 178 MB | 1.94 | 4.35 | 9.16 | 7.90 | 8.62 | 4.01 | 3.87 | 5.69 |
โ Open ASR Leaderboard's published row; the other rows were scored with its code on the full test sets, with Earnings-22 as the leaderboard's chunked set. The Phonon-2 row is the one published with its release.
Run it
Python 3.10 or newer (macOS's built-in python3 is 3.9).
pip install fermion-research
fermion transcribe phonon-2.5-en recording.wav
On Apple silicon, pip install "fermion-research[mlx]" runs the model on the GPU through MLX. On Linux (x86-64 and Arm) and
Windows the same package runs the CPU engine; on Linux, install torch from its CPU wheel index first to skip the GPU build:
pip install --no-deps torch --index-url https://download.pytorch.org/whl/cpu
pip install fermion-research
--json adds a start and end time for every word. fermion serve phonon-2.5-en --port 8010 starts an OpenAI-compatible
/v1/audio/transcriptions endpoint. The command line and
the server are documented at fermionresearch.com/docs/speech.
Notes
Based on parakeet-tdt-0.6b-v3 by NVIDIA; the tokenizer and output conventions (punctuation, casing, numerals) are the original's.
Licence CC-BY-4.0, same as the original; NOTICE lists the changes. The command line
and this repository's code are Apache 2.0.
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