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@ -54,7 +54,7 @@ both floating point and quantized inference.
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### Train a custom model
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A developer may choose to train a custom model using Tensorflow (see the
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[TensorFlow tutorials](../tutorials/) for examples of building and training
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[TensorFlow tutorials](https://www.tensorflow.org/tutorials/) for examples of building and training
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models). If you have already written a model, the first step is to export this
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to a `tf.GraphDef` file. This is required because some formats do not store the
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model structure outside the code, and we must communicate with other parts of
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@ -154,7 +154,7 @@ the arguments for specifying the output nodes for inference in the
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### Full converter reference
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The [TensorFlow Lite Converter](../convert.md) can be
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The [TensorFlow Lite Converter](../convert/index.md) can be
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[Python](../convert/python_api.md) or from the
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[command line](../convert/cmdline_examples.md). This allows you to integrate the
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conversion step into the model design workflow, ensuring the model is easy to
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