CLI for Omi Med STT v1 medical speech-to-text
Project description
Omi Med STT Runtime
Command-line runtime for Omi Med STT v1, an English medical speech-to-text model built from NVIDIA Parakeet TDT 0.6B v2.
The package downloads the right model artifact for your machine and transcribes audio locally.
Install
pip install -U omi-med-stt
Apple Silicon:
pip install -U "omi-med-stt[mlx]"
NVIDIA CUDA / NeMo:
pip install -U "omi-med-stt[nemo]"
Run
omi-med-stt audio.wav
Useful options:
omi-med-stt audio.wav --json
omi-med-stt audio.wav --runtime mlx
omi-med-stt audio.wav --runtime nemo
omi-med-stt audio.wav --runtime cpp
omi-med-stt check
Runtime Choices
| Platform | Default runtime | Model artifact |
|---|---|---|
| Apple Silicon | mlx |
omi-health/omi-med-stt-v1-mlx-q8 |
| NVIDIA CUDA | nemo |
omi-health/omi-med-stt-v1 |
| Linux/Windows CPU | cpp |
omi-health/omi-med-stt-v1-gguf |
The canonical model is the NeMo checkpoint. MLX and GGUF are runtime exports.
CPU setup:
omi-med-stt install-cpp --cpp-backend cpu
omi-med-stt audio.wav --runtime cpp
The CPU path uses a patched parakeet.cpp runtime and downloads the q8_0 GGUF
artifact only. It does not download the NeMo or MLX weights.
Runtime Quality
| Artifact | WER | M-WER | Drug M-WER | Medical Recall |
|---|---|---|---|---|
| NeMo canonical | 8.30% | 2.37% | 4.75% | 97.95% |
| MLX full precision | 8.59% | 2.65% | 5.20% | 97.70% |
| MLX q8 | 8.61% | 2.75% | 5.20% | 97.63% |
| GGUF q8_0 | 9.12% | 3.20% | 6.33% | 97.53% |
These numbers compare the released runtime artifacts against each other on the same internal benchmark. Visit omi.health for the broader model evaluation and product context.
Model Repositories
- Canonical NeMo:
omi-health/omi-med-stt-v1 - Apple Silicon q8:
omi-health/omi-med-stt-v1-mlx-q8 - Apple Silicon full precision:
omi-health/omi-med-stt-v1-mlx - Linux/Windows CPU GGUF:
omi-health/omi-med-stt-v1-gguf
If the model repositories are private before launch, authenticate first:
huggingface-cli login
CUDA Note
If --runtime nemo fails with a CUDA driver mismatch, install a PyTorch wheel
matching your driver before installing the NeMo extra. For example, on CUDA 12.8
hosts:
pip install torch --index-url https://download.pytorch.org/whl/cu128
pip install -U "omi-med-stt[nemo]"
Development
git clone https://github.com/Omi-Health/omi-med-stt-runtime
cd omi-med-stt-runtime
pip install -e ".[dev]"
python scripts/prepublish_check.py --skip-build
python -m pytest -q tests
Safety
Omi Med STT v1 is speech-to-text only. It is not a diagnostic, triage, prescribing, or clinical decision model, and it is not clinically validated. Transcripts must be reviewed before any clinical use.
License And Attribution
Runtime code is MIT licensed.
Model weights are CC-BY-4.0 and are derived from
nvidia/parakeet-tdt-0.6b-v2.
Omi Med STT v1 is not an NVIDIA model.
The CPU runtime uses parakeet.cpp.
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