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
Update metadata
Browse files- SHA256SUMS.txt +1 -1
- packed_manifest.json +1 -12
SHA256SUMS.txt
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98125795b6dda72f5c6eee9ba33d19815df65dcb18b50a357bf9f73c9935309e phonon-2.bps.tar.zst
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422379e411f14dde97174554deead106ec1e4816e14dd78a1bf99517c6dcc663 config.json
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00624a5043e7ce74029317b024132ca5286116d6fbf3191d226374bc8273789f NOTICE
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8481cfc11537e6dc1e40a8296c93aa15f9b7437b1514564caf647f8773c0dcb3 reference_transformers.py
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5cf172e8cf6b313e951c4ef588ca913c7285b0aa3b92de413c3d7ec2b939c0e4 fermion_container.py
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98125795b6dda72f5c6eee9ba33d19815df65dcb18b50a357bf9f73c9935309e phonon-2.bps.tar.zst
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422379e411f14dde97174554deead106ec1e4816e14dd78a1bf99517c6dcc663 config.json
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399e9397cf7415130a0d612b221bc8a37b91c29caafe5e0b20c515d317ffb308 packed_manifest.json
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00624a5043e7ce74029317b024132ca5286116d6fbf3191d226374bc8273789f NOTICE
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8481cfc11537e6dc1e40a8296c93aa15f9b7437b1514564caf647f8773c0dcb3 reference_transformers.py
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5cf172e8cf6b313e951c4ef588ca913c7285b0aa3b92de413c3d7ec2b939c0e4 fermion_container.py
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packed_manifest.json
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{
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"format": "fermion-five-value-parakeet-v1",
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"status": "PASS",
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"container": "model.fermion",
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"container_sha256": "4b6bfa3a12cc3c4e0a54f2ab3ec4ca7a842b09e5c7ecfc8e7ca0ac6cc8c11468",
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"container_bytes": 177438361,
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"five_value_modules": 264,
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"dense_tables": "int6",
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"bits_per_plane": 2,
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"planes": 2,
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"base_model": "nvidia/parakeet-tdt-0.6b-v3",
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"license": "cc-by-4.0"
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"gates": {
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"G-PLANE": "max abs delta 0.0 on 264/264 (mlx dequantize vs exact five-value expansion), 2026-09-25",
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"G-LOAD": "explicit key-set check, 697/697 names, 0 missing / 0 unexpected",
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"G-DECODE mlx-vs-mlx": "40/40 LibriSpeech utterances identical text and tokens (bf16 packed vs fp32 dense), 2026-09-26"
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}
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}
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{
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"container": "model.fermion",
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"container_sha256": "4b6bfa3a12cc3c4e0a54f2ab3ec4ca7a842b09e5c7ecfc8e7ca0ac6cc8c11468",
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"container_bytes": 177438361,
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"base_model": "nvidia/parakeet-tdt-0.6b-v3",
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"license": "cc-by-4.0"
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}
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