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Ikko Eltociear Ashimine
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Fix typo in 04-onnx-export.ipynb (#44)
accross -> across
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examples/NLU/notebooks/04-onnx-export.ipynb

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"[ONNX](http://onnx.ai/) is open format for machine learning models. It allows to save your neural network's computation graph in a framework agnostic way, which might be particulary helpful when deploying deep learning models.\n",
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"Indeed, businesses might have other requirements _(languages, hardware, ...)_ for which the training framework might not be the best suited in inference scenarios. In that context, having a representation of the actual computation graph that can be shared accross various business units and logics across an organization might be a desirable component.\n",
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"Indeed, businesses might have other requirements _(languages, hardware, ...)_ for which the training framework might not be the best suited in inference scenarios. In that context, having a representation of the actual computation graph that can be shared across various business units and logics across an organization might be a desirable component.\n",
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"Along with the serialization format, ONNX also provides a runtime library which allows efficient and hardware specific execution of the ONNX graph. This is done through the [onnxruntime](https://microsoft.github.io/onnxruntime/) project and already includes collaborations with many hardware vendors to seamlessly deploy models on various platforms.\n",
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