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Install TensorFlow 2
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devsite-landing-row-1-up devsite-landing-row-large-headings devsite-landing-row-50 " header-position="top" > <div class="devsite-landing-row-inner"> <div class="devsite-landing-row-group"> <div class="devsite-landing-row-item" description-position="bottom" > <div class="devsite-landing-row-item-media "> <div class="devsite-landing-row-item-code"> <pre class="prettyprint lang-bsh devsite-disable-click-to-copy" translate="no" dir="ltr"> # Requires the latest pip <code class="devsite-terminal" translate="no" dir="ltr">pip install --upgrade pip</code><br/> # Current stable release for CPU and GPU <code class="devsite-terminal" translate="no" dir="ltr">pip install tensorflow</code><br/> # Or try the preview build (unstable) <code class="devsite-terminal" translate="no" dir="ltr">pip install tf-nightly</code><br/> </div> </div> <div class="devsite-landing-row-item-description" > <div class="devsite-landing-row-item-body"> <h3 id="download-a-package" data-text="Download a package" class="hide-from-toc no-link" tabindex="0"> <a href="https://www.tensorflow.org/install/pip"> Download a package </a> </h3> <div class="devsite-landing-row-item-description-content"> <p>Install TensorFlow with Python's <em>pip</em> package manager.</p> <aside class="note">TensorFlow 2 packages require a <code translate="no" dir="ltr">pip</code> version >19.0 (or >20.3 for macOS).</aside> <p>Official packages available for Ubuntu, Windows, and macOS.</p> </div> <div class="devsite-landing-row-item-buttons"> <a href="https://www.tensorflow.org/install/pip" class="button button-primary " >Read the pip install guide</a> </div> </div> </div> </div> </div> </div> </section> <section class="devsite-landing-row devsite-landing-row-1-up devsite-landing-row-100 devsite-landing-row-large-headings" header-position="top" > <div class="devsite-landing-row-inner"> <div class="devsite-landing-row-group"> <div class="devsite-landing-row-item devsite-landing-row-item-no-media" description-position="bottom" > <div class="devsite-landing-row-item-description" > <div class="devsite-landing-row-item-body"> <h3 id="run-a-tensorflow-container" data-text="Run a TensorFlow container" class="hide-from-toc no-link" tabindex="0"> <a href="https://www.tensorflow.org/install/docker"> Run a TensorFlow container </a> </h3> <div class="devsite-landing-row-item-description-content"> <p> The <a href="https://hub.docker.com/r/tensorflow/tensorflow/" class="external">TensorFlow Docker images</a> are already configured to run TensorFlow. A <a href="https://docs.docker.com/install/" class="external">Docker</a> container runs in a virtual environment and is the easiest way to set up GPU support. </p> <pre class="prettyprint lang-bsh" translate="no" dir="ltr"> <code class="devsite-terminal" translate="no" dir="ltr">docker pull tensorflow/tensorflow:latest # Download latest stable image</code><br/> <code class="devsite-terminal" translate="no" dir="ltr">docker run -it -p 8888:8888 tensorflow/tensorflow:latest-jupyter # Start Jupyter server</code> </pre> </div> <div class="devsite-landing-row-item-buttons"> <a href="https://www.tensorflow.org/install/docker" class="button button-primary " >Read the Docker install guide</a> </div> </div> </div> </div> </div> </div> </section> <section class="devsite-landing-row devsite-landing-row-1-up devsite-landing-row-large-headings devsite-landing-row-100" header-position="top" > <div class="devsite-landing-row-inner"> <div class="devsite-landing-row-group"> <div class="devsite-landing-row-item devsite-landing-row-item-no-media" description-position="bottom" > <div class="devsite-landing-row-item-description" > <div class="devsite-landing-row-item-body"> <h3 id="google-colab58-an-easy-way-to-learn-and-use-tensorflow" data-text="Google Colab: An easy way to learn and use TensorFlow" class="hide-from-toc no-link" tabindex="0"> Google Colab: An easy way to learn and use TensorFlow </h3> <div class="devsite-landing-row-item-description-content"> <p> No install necessary—run the <a href="/tutorials">TensorFlow tutorials</a> directly in the browser with <a href="https://colab.research.google.com/notebooks/welcome.ipynb" class="external">Colaboratory</a>, a Google research project created to help disseminate machine learning education and research. It's a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud. <a href="https://medium.com/tensorflow/colab-an-easy-way-to-learn-and-use-tensorflow-d74d1686e309" class="external">Read the blog post</a>. </p> </div> </div> </div> </div> </div> </div> </section> <section class="devsite-landing-row devsite-landing-row-2-up" background="grey" header-position="top" > <div class="devsite-landing-row-inner"> <header class="devsite-landing-row-header" > <div class="devsite-landing-row-header-text"> <h2 id="build-your-first-ml-app" data-text="Build your first ML app" tabindex="0"> Build your first ML app </h2> <div class="devsite-landing-row-description"> Create and deploy TensorFlow models on web and mobile. </div> </div> </header> <div class="devsite-landing-row-group"> <div class="devsite-landing-row-item devsite-landing-row-item-no-media tfo-landing-row-item-inset-white" description-position="bottom" > <div class="devsite-landing-row-item-description" > <div class="devsite-landing-row-item-body"> <h3 id="web-developers" data-text="Web developers" class="hide-from-toc no-link" tabindex="0"> <a href="https://js.tensorflow.org"> Web developers </a> </h3> <div class="devsite-landing-row-item-description-content"> TensorFlow.js is a WebGL accelerated, JavaScript library to train and deploy ML models in the browser, Node.js, mobile, and more. </div> </div> </div> </div> <div class="devsite-landing-row-item devsite-landing-row-item-no-media tfo-landing-row-item-inset-white" description-position="bottom" > <div class="devsite-landing-row-item-description" > <div class="devsite-landing-row-item-body"> <h3 id="mobile-developers" data-text="Mobile developers" class="hide-from-toc no-link" tabindex="0"> <a href="https://www.tensorflow.org/lite"> Mobile developers </a> </h3> <div class="devsite-landing-row-item-description-content"> TensorFlow Lite is a lightweight solution for mobile and embedded devices. </div> </div> </div> </div> </div> </div> </section> </div> <div class="devsite-floating-action-buttons"> </div> </article> <devsite-content-footer class="nocontent"> <p>Except as otherwise noted, the content of this page is licensed under the <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 License</a>, and code samples are licensed under the <a href="https://www.apache.org/licenses/LICENSE-2.0">Apache 2.0 License</a>. 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