Automatic Speech Recognition
MLX
English
parakeet_tdt_five_value
apple-silicon
speech-to-text
asr
stt
on-device
Eval Results
Instructions to use FermionResearch/Phonon-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use FermionResearch/Phonon-2 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download FermionResearch/Phonon-2 --local-dir Phonon-2
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Phonon-2 card: about 2.1 bits per stored encoder weight
Browse files- README.md +1 -1
- SHA256SUMS.txt +1 -1
README.md
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@@ -25,7 +25,7 @@ Phonon-2 is the most accurate open speech recognition model for English under 90
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seven English sets it averages 5.21 % word error, and every open model that scores better is at least 5.8 times its size.
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Set for set it holds the accuracy of its 2.5 GB full-precision teacher, reaching 100.8 % of the teacher's word accuracy on
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parliamentary speech and beating it on meetings, from a download 15 times smaller. Its encoder holds each weight at one of
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five learned levels in
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It transcribes an hour of audio in about 20 seconds on an M5 MacBook Air (174x realtime), at 143x on eight Zen 5 cores
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(16 vCPU) and at 6,680x on one H100 in batches of 128.
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seven English sets it averages 5.21 % word error, and every open model that scores better is at least 5.8 times its size.
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Set for set it holds the accuracy of its 2.5 GB full-precision teacher, reaching 100.8 % of the teacher's word accuracy on
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parliamentary speech and beating it on meetings, from a download 15 times smaller. Its encoder holds each weight at one of
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five learned levels in about 2.1 bits.
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It transcribes an hour of audio in about 20 seconds on an M5 MacBook Air (174x realtime), at 143x on eight Zen 5 cores
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(16 vCPU) and at 6,680x on one H100 in batches of 128.
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SHA256SUMS.txt
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00624a5043e7ce74029317b024132ca5286116d6fbf3191d226374bc8273789f NOTICE
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6833410ae75725ec2a9392085c2138a6d4ffb87be62ff5fe86faff45413f8586 reference_transformers.py
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5cf172e8cf6b313e951c4ef588ca913c7285b0aa3b92de413c3d7ec2b939c0e4 fermion_container.py
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-
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9ba9550ad48438d0836ddab3da480b3b69ffa0aac7b7878b5a0039e7ab429411 LICENSE-WEIGHTS-CC-BY-4.0.txt
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cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30 LICENSE-CODE-Apache-2.0.txt
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00624a5043e7ce74029317b024132ca5286116d6fbf3191d226374bc8273789f NOTICE
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6833410ae75725ec2a9392085c2138a6d4ffb87be62ff5fe86faff45413f8586 reference_transformers.py
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5cf172e8cf6b313e951c4ef588ca913c7285b0aa3b92de413c3d7ec2b939c0e4 fermion_container.py
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0dad36aa73a9b80fd5165dc33bd226f874a4ff727b06c7bd04a289c69da58452 README.md
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9ba9550ad48438d0836ddab3da480b3b69ffa0aac7b7878b5a0039e7ab429411 LICENSE-WEIGHTS-CC-BY-4.0.txt
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cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30 LICENSE-CODE-Apache-2.0.txt
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