# Convert using offline converter tool (CLI)

Source: [https://docs.qualcomm.com/doc/80-70014-54/topic/convert-using-offline-converter-tool-cli.html](https://docs.qualcomm.com/doc/80-70014-54/topic/convert-using-offline-converter-tool-cli.html)

The TensorFlow Lite converter tool, tflite\_convert, which can be used offline, is
        included in the TensorFlow pip package for TensorFlow versions 2.x and above.

The tflite\_convert tool accepts the following input in the CLI:

    tflite_convert --help
    
    optional arguments:
      -h, --help            show this help message and exit
      --output_file OUTPUT_FILE
                            Full filepath of the output file.
      --saved_model_dir SAVED_MODEL_DIR
                            Full path of the directory containing the SavedModel.
      --keras_model_file KERAS_MODEL_FILE
                            Full filepath of HDF5 file containing tf.Keras model.
      --saved_model_tag_set SAVED_MODEL_TAG_SET
                            Comma-separated set of tags identifying the MetaGraphDef within the SavedModel to analyze. All tags must be present. To pass in an empty
                            tag set, pass in "". (default "serve")
      --saved_model_signature_key SAVED_MODEL_SIGNATURE_KEY
                            Key identifying the SignatureDef containing inputs and outputs. (default DEFAULT_SERVING_SIGNATURE_DEF_KEY)
      --enable_v1_converter
                            Enables the TensorFlow V1 converter in 2.0
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## Convert a SavedModel

To convert a typical TensorFlow model saved in the saved\_model format using the
                tflite\_convert tool, run the following command:

    tflite_convert \    --saved_model_dir=/tmp/mobilenet_saved_model \    --output_file=/tmp/mobilenet.tflite \  --saved_model_tag_set=serve \
             --saved_model_signature_key=”serving_default”
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## Converting a Keras H5 model

To convert a Keras model using the tflite\_convert tool, run the following
                command:

    tflite_convert \
      --keras_model_file=/tmp/mobilenet_keras_model.h5 \
      --output_file=/tmp/mobilenet.tflite
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Note: The tflite\_convert tool is for basic purposes only. Python
                APIs are recommended for posttraining integer quantization.

**Parent Topic:** [Convert a TensorFlow or Keras model to TensorFlow Lite format](https://docs.qualcomm.com/doc/80-70014-54/topic/convert-a-tensorflow-or-keras-model-to-tensorflow-lite-format.html)

Last Published: Jul 12, 2024

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