# Converting an ONNX Model¶

## Introduction to ONNX¶

ONNX* is a representation format for deep learning models. ONNX allows AI developers easily transfer models between different frameworks that helps to choose the best combination for them. Today, PyTorch*, Caffe2*, Apache MXNet*, Microsoft Cognitive Toolkit* and other tools are developing ONNX support.

## Convert an ONNX* Model¶

The Model Optimizer process assumes you have an ONNX model that was directly downloaded from a public repository or converted from any framework that supports exporting to the ONNX format.

To convert an ONNX* model, run Model Optimizer with the path to the input model .onnx file:

mo --input_model <INPUT_MODEL>.onnx

There are no ONNX* specific parameters, so only framework-agnostic parameters are available to convert your model. For details, see the General Conversion Parameters section on the Converting a Model to Intermediate Representation (IR) page.

## Supported ONNX* Layers¶

Refer to Supported Framework Layers for the list of supported standard layers.