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tensorflow/lite/g3doc/guide/python.md

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+# Quickstart for Linux-based devices with Python
+
+Using TensorFlow Lite with Python is great for embedded devices based on Linux,
+such as [Raspberry Pi](https://www.raspberrypi.org/){:.external} and
+[Coral devices with Edge TPU](https://coral.withgoogle.com/){:.external},
+among many others.
+
+This page shows how you can start running TensorFlow Lite models with Python in
+just a few minutes. All you need is a TensorFlow model [converted to TensorFlow
+Lite](../models/convert/). (If you don't have a model converted yet, you can
+experiment using the model provided with the example linked below.)
+
+## About the TensorFlow Lite runtime package
+
+To quickly start executing TensorFlow Lite models with Python, you can install
+just the TensorFlow Lite interpreter, instead of all TensorFlow packages. We
+call this simplified Python package `tflite_runtime`.
+
+The `tflite_runtime` package is a fraction the size of the full `tensorflow`
+package and includes the bare minimum code required to run inferences with
+TensorFlow Lite—primarily the
+[`Interpreter`](https://www.tensorflow.org/api_docs/python/tf/lite/Interpreter)
+Python class. This small package is ideal when all you want to do is execute
+`.tflite` models and avoid wasting disk space with the large TensorFlow library.
+
+Note: If you need access to other Python APIs, such as the
+[TensorFlow Lite Converter](../models/convert/), you must install the
+[full TensorFlow package](https://www.tensorflow.org/install/).
+For example, the [Select TF ops]
+(https://www.tensorflow.org/lite/guide/ops_select) are not included in the
+`tflite_runtime` package. If your models have any dependencies to the Select TF
+ops, you need to use the full TensorFlow package instead.
+
+## Install TensorFlow Lite for Python
+
+You can install on Linux with pip:
+
+<pre class="devsite-terminal devsite-click-to-copy">
+python3 -m pip install tflite-runtime
+</pre>
+
+## Supported platforms
+
+The `tflite-runtime` Python wheels are pre-built and provided for these
+platforms:
+* Linux armv7l (e.g. Raspberry Pi 2, 3, 4 and Zero 2 running Raspberry Pi OS
+  32-bit)
+* Linux aarch64 (e.g. Raspberry Pi 3, 4 running Debian ARM64)
+* Linux x86_64
+
+If you want to run TensorFlow Lite models on other platforms, you should either
+use the [full TensorFlow package](https://www.tensorflow.org/install/), or
+[build the tflite-runtime package from source](build_cmake_pip.md).
+
+If you're using TensorFlow with the Coral Edge TPU, you should
+instead follow the appropriate [Coral setup documentation](https://coral.ai/docs/setup).
+
+Note: We no longer update the Debian package `python3-tflite-runtime`. The
+latest Debian package is for TF version 2.5, which you can install by following
+[these older instructions](https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/lite/g3doc/guide/python.md#install-tensorflow-lite-for-python).
+
+Note: We no longer release pre-built `tflite-runtime` wheels for Windows and
+macOS. For these platforms, you should use the
+[full TensorFlow package](https://www.tensorflow.org/install/), or
+[build the tflite-runtime package from source](build_cmake_pip.md).
+
+## Run an inference using tflite_runtime
+
+Instead of importing `Interpreter` from the `tensorflow` module, you now need to
+import it from `tflite_runtime`.
+
+For example, after you install the package above, copy and run the
+[`label_image.py`](
+https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/examples/python/)
+file. It will (probably) fail because you don't have the `tensorflow` library
+installed. To fix it, edit this line of the file:
+
+```python
+import tensorflow as tf
+```
+
+So it instead reads:
+
+```python
+import tflite_runtime.interpreter as tflite
+```
+
+And then change this line:
+
+```python
+interpreter = tf.lite.Interpreter(model_path=args.model_file)
+```
+
+So it reads:
+
+```python
+interpreter = tflite.Interpreter(model_path=args.model_file)
+```
+
+Now run `label_image.py` again. That's it! You're now executing TensorFlow Lite
+models.
+
+## Learn more
+
+* For more details about the `Interpreter` API, read
+  [Load and run a model in Python](inference.md#load-and-run-a-model-in-python).
+
+* If you have a Raspberry Pi, check out a [video series](https://www.youtube.com/watch?v=mNjXEybFn98&list=PLQY2H8rRoyvz_anznBg6y3VhuSMcpN9oe)
+  about how to run object detection on Raspberry Pi using TensorFlow Lite.
+
+* If you're using a Coral ML accelerator, check out the
+  [Coral examples on GitHub](https://github.com/google-coral/tflite/tree/master/python/examples).
+
+* To convert other TensorFlow models to TensorFlow Lite, read about the
+  [TensorFlow Lite Converter](../models/convert/).
+
+* If you want to build `tflite_runtime` wheel, read
+  [Build TensorFlow Lite Python Wheel Package](build_cmake_pip.md)