= ONNX
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The most important thing this project provides appears to be the `.onnx` file format, which represents <ANN models>, pre-trained or not.
<Deep learning frameworks> can then output such `.onnx` files for interchangeability and serialization.
Some examples:
* <activatedgeek LeNet-5> produces a trained `.onnx` from <PyTorch>
* <MLperf v2.1 ResNet> can use `.onnx` as a pre-trained model
The cool thing is that <ONNX> can then run <inference> in an uniform manner on a variety of devices without installing the <deep learning framework> used for. It's a bit like having a kind of portable executable. Neat.
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