TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile devices.
This PyPI package includes the Python bindings for following features:
- Task Library: a set of powerful and easy-to-use task-specific libraries to
integrate TFLite models onto various platforms. See the [Task Library
documentation](https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview)
for more information.
- Metadata schemas: wraps TFLite model schema and metadata schema in Python.
- Metadata writer and displayer: can be used to populate the metadata and
associated files into the model, as well as converting the populated metadata
into the json format. See the [Metadata
documentation](https://www.tensorflow.org/lite/convert/metadata) for more
information.
- Android Codegen tool: generates the Java model interface used in Android for
a particular model. See the [Codegen tool
documentation](https://www.tensorflow.org/lite/inference_with_metadata/codegen)
for more information.
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