Model: canary-v2-int8
Original model: NVIDIA Corporation, https://huggingface.co/nvidia/canary-1b-v2
ONNX export: Ilya Stupakov, https://huggingface.co/istupakov/canary-1b-v2-onnx
Revision: 5ebc1520cef7b6b318b3526ad17adbfe00bc1bfc
Source: https://huggingface.co/istupakov/canary-1b-v2-onnx/tree/5ebc1520cef7b6b318b3526ad17adbfe00bc1bfc
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
https://creativecommons.org/licenses/by/4.0/

This is the upstream ONNX export with int8 quantized weights, selected without
changes to the downloaded files. TBridge supplies a separate speech-model.json
configuration. The model is not covered by the TBridge Perimeter license.
The authors do not endorse TBridge. See the accompanying CC-BY-4.0.txt.

Upstream model card (unchanged):

---
license: cc-by-4.0
language:
- bg
- hr
- cs
- da
- nl
- en
- et
- fi
- fr
- de
- el
- hu
- it
- lv
- lt
- mt
- pl
- pt
- ro
- sk
- sl
- es
- sv
- ru
- uk
base_model:
- nvidia/canary-1b-v2
pipeline_tag: automatic-speech-recognition
tags:
- automatic-speech-recognition
- automatic-speech-translation
- asr
- onnx
- onnx-asr
---

NVIDIA Canary 1B v2 [model](https://huggingface.co/nvidia/canary-1b-v2) converted to ONNX format for [onnx-asr](https://github.com/istupakov/onnx-asr).

Install onnx-asr
```shell
pip install onnx-asr[cpu,hub]
```

Load Canary 1B v2 model and recognize wav file
```py
import onnx_asr
model = onnx_asr.load_model("nemo-canary-1b-v2")
print(model.recognize("test.wav", language="en"))
print(model.recognize("test.wav", language="en", target_language="fr"))
```