google-cloud/pr_98/en/containers/introduction.html

<meta charset="utf-8" /><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Introduction&quot;,&quot;local&quot;:&quot;introduction&quot;,&quot;sections&quot;:[],&quot;depth&quot;:1}">
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		<link rel="modulepreload" href="/docs/google-cloud/pr_98/en/_app/immutable/chunks/EditOnGithub.d2d81eda.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Introduction&quot;,&quot;local&quot;:&quot;introduction&quot;,&quot;sections&quot;:[],&quot;depth&quot;:1}"><!-- HEAD_svelte-u9bgzb_END -->      <p></p>  <h1 class="relative group"><a id="introduction" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#introduction"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Introduction</span></h1> <p data-svelte-h="svelte-19g98k1">Hugging Face built Deep Learning Containers (DLCs) for Google Cloud customers to run any of their machine learning workload in an optimized environment, with no configuration or maintenance on their part. These are Docker images pre-installed with deep learning frameworks and libraries such as 🤗 Transformers, 🤗 Datasets, and 🤗 Tokenizers. The DLCs allow you to directly serve and train any models, skipping the complicated process of building and optimizing your serving and training environments from scratch.</p> <p data-svelte-h="svelte-1r80009">The containers are publicly maintained, updated and released periodically by Hugging Face and the Google Cloud Team and available for all Google Cloud Customers within the <a href="https://console.cloud.google.com/artifacts/docker/deeplearning-platform-release/us/gcr.io" rel="nofollow">Google Cloud’s Artifact Registry</a>. They can be used from any Google Cloud service such as:</p> <ul data-svelte-h="svelte-1cz224m"><li><a href="(https://cloud.google.com/vertex-ai/docs)">Vertex AI</a>: Vertex AI is a Machine Learning (ML) platform that lets you train and deploy ML models and AI applications, and customize Large Language Models (LLMs).</li> <li><a href="https://cloud.google.com/kubernetes-engine/docs" rel="nofollow">Google Kubernetes Engine</a> (GKE): GKE is a fully-managed Kubernetes service in Google Cloud that can be used to deploy and operate containerized applications at scale using Google Cloud’s infrastructure.</li> <li><a href="https://cloud.google.com/run/docs" rel="nofollow">Cloud Run</a> (in preview): Cloud Run is a serverless managed compute platform that enables you to run containers that are invocable via requests or events.</li></ul> <p data-svelte-h="svelte-13wm61o">We are curating a list of <a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples" rel="nofollow">notebook examples</a> on how to programmaticaly train and deploy models on these Google Cloud services.</p> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/Google-Cloud-Containers/blob/main/docs/source/containers/introduction.mdx" target="_blank"><span data-svelte-h="svelte-1kd6by1">&lt;</span> <span data-svelte-h="svelte-x0xyl0">&gt;</span> <span data-svelte-h="svelte-1dajgef"><span class="underline ml-1.5">Update</span> on GitHub</span></a>  <p></p> 
			
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