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TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile / ioT devices.

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Hi! Is the [tflite_runtime](https://pypi.org/project/tflite-runtime/) package required to run TF-Lite with Coral, or should we use `tf.lite`, as part of the `tensorflow` Python library? Thank you! Related: Are there any examples...

I am getting the following error while loading the input and output audio buffers to tensorflow-lite interpreter for inferencing. I am using the TensorAudio and TensorAudioFormat packages from the tflite-support.audio...

I see code in wav_io.cc. That has read wav code.

![image](https://user-images.githubusercontent.com/10862253/204266339-3db9c2de-6f27-4a53-9423-deb11a0c1495.png)

implementation 'org.tensorflow:tensorflow-lite-support:0.1.0' Why do I run this instruction to generate two dependent libraries, TensorFlow Lite and TensorFlow Lite Support? How can I generate only tensorflow site support as a dependency...

How to modify the quant_scale and zero_point of quantized tflite model? Seems we could only read these values for now.

Could you please provide a `manylinux2014_aarch64` wheel for python 3.11 on pypi?` I saw the x86 wheels there but these aren't of use to me.

I'm trying to classify text into one of 20 categories (20newsgroups dataset). I have a tflite model that I use to make inference. The inference is made with BertNLClassifier.classify() method....