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TensorFlow Lite converter
The TensorFlow Lite converter takes a TensorFlow model and generates a
TensorFlow Lite FlatBuffer file
(.tflite). The converter supports
SavedModel directories,
tf.keras models, and
concrete functions.
Note: This page contains documentation on the converter API for TensorFlow 2.0. The API for TensorFlow 1.X is available here.
Device deployment
The TensorFlow Lite FlatBuffer file is then deployed to a client device (e.g.
mobile, embedded) and run locally using the TensorFlow Lite interpreter. This
conversion process is shown in the diagram below:
Converting models
The TensorFlow Lite converter should be used from the Python API. Using the Python API makes it easier to convert models as part of a model development pipeline and helps mitigate compatibility issues early on. Alternatively, the command line tool supports basic models.