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A lightweight Python package for Automatic Speech Recognition using ONNX models
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| 2026-07-31 | 354 |
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| 2026-11-04 | 387 |
Today
— stars today
This week
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+5 stars this month
Momentum
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growth rate 0.00%/day
# ONNX ASR
[](https://pypi.org/project/onnx-asr)
[](https://pypi.org/project/onnx-asr)
[](https://pypi.org/project/onnx-asr)
[](https://pypi.org/project/onnx-asr)
[](https://github.com/istupakov/onnx-asr/blob/main/LICENSE)<br>
[](https://github.com/astral-sh/uv)
[](https://github.com/astral-sh/ruff)
[](https://mypy-lang.org/)
[](https://squidfunk.github.io/mkdocs-material/)
[](https://www.codefactor.io/repository/github/istupakov/onnx-asr/overview/main)
[](https://codecov.io/github/istupakov/onnx-asr)
[](https://github.com/istupakov/onnx-asr/actions/workflows/python-package.yml)
**onnx-asr** is a Python package for Automatic Speech Recognition using ONNX models. It's a lightweight, fast, and easy-to-use pure Python package with minimal dependencies (no need for PyTorch, Transformers, or FFmpeg):
[](https://pypi.org/project/numpy/)
[](https://pypi.org/project/onnxruntime/)
[](https://pypi.org/project/huggingface-hub/)
Key features of **onnx-asr** include:
* Supports many modern ASR [models](https://istupakov.github.io/onnx-asr/usage/#supported-model-names)
* Runs on a wide range of devices, from small IoT/edge devices to servers with powerful GPUs ([benchmarks](https://istupakov.github.io/onnx-asr/benchmarks/))
* Works on Windows, Linux, and macOS on x86 and Arm CPUs, with support for CUDA, TensorRT, CoreML, DirectML, ROCm, and WebGPU
* Supports NumPy versions from 1.23.5 to 2.5+ and Python versions from 3.11 to 3.14
* Loads models from Hugging Face or local directories, including quantized versions
* Accepts WAV files or NumPy arrays, with built-in file reading and resampling
* Supports custom models (see the [Conversion Guide](https://istupakov.github.io/onnx-asr/conversion/) for instructions)
* Supports batch processing
* Supports long-form recognition using [VAD](https://istupakov.github.io/onnx-asr/usage/#vad-voice-activity-detection) (Voice Activity Detection)
* Can return token-level timestamps and log probabilities
* Provides a fully typed and well-documented [Python API](https://istupakov.github.io/onnx-asr/reference/)
* Provides a simple command-line interface ([CLI](https://istupakov.github.io/onnx-asr/usage/#cli))
> [!NOTE]
> Supports **Parakeet v2 (En) / v3 (Multilingual)**, **Canary v1/v2 (Multilingual)**, **GigaAM v2/v3 (Ru)**, and **GigaAM Multilingual** models!
> [!TIP]
> Try the onnx-asr demo on Hugging Face Spaces:
>
> [](https://istupakov-onnx-asr.hf.space/)
## Quick Start
Install onnx-asr:
```sh
pip install onnx-asr[cpu,hub]
```
Load a model and recognize a WAV file:
```py
import onnx_asr
# Load the Parakeet TDT v3 model from Hugging Face (may take a few minutes)
model = onnx_asr.load_model("neExcerpt of 7,096 characters
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