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|[TensorFlow](https://www.tensorflow.org/)|[onnx/onnx-tensorflow](https://github.com/onnx/onnx-tensorflow) and [onnx/tensorflow-onnx](https://github.com/onnx/tensorflow-onnx)|[Exporting - ONNX-Tensorflow](tutorials/OnnxTensorflowExport.ipynb)<br>[Exporting - Tensorflow-ONNX](https://github.com/onnx/tensorflow-onnx/blob/master/examples/call_coverter_via_python.py)|[Importing](tutorials/OnnxTensorflowImport.ipynb)[experimental]|
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|[TensorFlow](https://www.tensorflow.org/)|[onnx/onnx-tensorflow](https://github.com/onnx/onnx-tensorflow) and [onnx/tensorflow-onnx](https://github.com/onnx/tensorflow-onnx)|[Exporting](https://github.com/onnx/tensorflow-onnx/blob/master/examples/call_coverter_via_python.py)|[Importing](tutorials/OnnxTensorflowImport.ipynb)|
* Use services like [Azure Custom Vision service](https://docs.microsoft.com/en-us/azure/cognitive-services/Custom-Vision-Service/custom-vision-onnx-windows-ml) that generate customized ONNX models for your data
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