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younghan-meta/Parakeet-TDT-ExecuTorch-MLX

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Parakeet-TDT-ExecuTorch-MLX

Pre-exported ExecuTorch .pte file for Parakeet TDT 0.6B with the MLX backend on Apple Silicon.

This variant uses:

  • —MLX delegate
  • —bf16 activations
  • —4-bit weight-only quantization for encoder and decoder linear layers
  • —group size 128

For the Metal (Apple GPU) variant, see Parakeet-TDT-ExecuTorch-Metal.

Installation

bash
git clone https://github.com/pytorch/executorch/ ~/executorch
cd ~/executorch
make parakeet-mlx

Download

bash
hf download younghan-meta/Parakeet-TDT-ExecuTorch-MLX --local-dir ~/parakeet_mlx

Run

bash
cmake-out/examples/models/parakeet/parakeet_runner \
  --model_path ~/parakeet_mlx/model.pte \
  --tokenizer_path ~/parakeet_mlx/tokenizer.model \
  --audio_path /path/to/audio.wav \
  --timestamps none

Optional flags:

  • —--timestamps segment for segment timestamps
  • —--timestamps word for word timestamps
  • —--timestamps all for token, word, and segment timestamps

Export Command

bash
pip install "nemo_toolkit[asr]"
python examples/models/parakeet/export_parakeet_tdt.py \
    --backend mlx \
    --dtype bf16 \
    --qlinear_encoder 4w \
    --qlinear_encoder_group_size 128 \
    --qlinear 4w \
    --qlinear_group_size 128 \
    --output-dir ./parakeet_mlx

This export produces:

  • —model.pte
  • —tokenizer.model

No separate delegate data blob is required for MLX.

License and attribution

The files are derived from `nvidia/parakeet-tdt-0.6b-v3` revision 541d1f99c6b0c3cd0b11a95167540bb8edefd82b and remain subject to CC-BY-4.0. The model was converted to the ExecuTorch PTE format for the MLX backend; it was not retrained or fine-tuned. See LICENSE and NOTICE.md.

For reproducible applications, download from the immutable repository revision recorded in the consuming application's artifact manifest and verify the exact size and SHA-256 from manifest.json.

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