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<meta charset="utf-8" /><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Hugging Face on Google Cloud&quot;,&quot;local&quot;:&quot;hugging-face-on-google-cloud&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Train and Deploy Models on Google Cloud with Hugging Face Deep Learning Containers&quot;,&quot;local&quot;:&quot;train-and-deploy-models-on-google-cloud-with-hugging-face-deep-learning-containers&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2}],&quot;depth&quot;:1}">
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		<link rel="modulepreload" href="/docs/google-cloud/pr_113/en/_app/immutable/chunks/EditOnGithub.d1c48e3d.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Hugging Face on Google Cloud&quot;,&quot;local&quot;:&quot;hugging-face-on-google-cloud&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Train and Deploy Models on Google Cloud with Hugging Face Deep Learning Containers&quot;,&quot;local&quot;:&quot;train-and-deploy-models-on-google-cloud-with-hugging-face-deep-learning-containers&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2}],&quot;depth&quot;:1}"><!-- HEAD_svelte-u9bgzb_END -->      <p></p>  <h1 class="relative group"><a id="hugging-face-on-google-cloud" 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="#hugging-face-on-google-cloud"><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>Hugging Face on Google Cloud</span></h1> <p data-svelte-h="svelte-5bmp1t"><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/google-cloud/thumbnail.png" alt="Hugging Face x Google Cloud"></p> <p data-svelte-h="svelte-1xc3l3u">Hugging Face collaborates with Google across open science, open source, cloud, and hardware to enable companies to build their own AI with the latest open models from Hugging Face and the latest cloud and hardware features from Google Cloud.</p> <p data-svelte-h="svelte-15of9o9">Hugging Face enables new experiences for Google Cloud customers. They can easily train and deploy Hugging Face models on Google Kubernetes Engine (GKE) and Vertex AI, on any hardware available in Google Cloud using Hugging Face Deep Learning Containers (DLCs).</p> <p data-svelte-h="svelte-18g7ow5">If you have any issues using Hugging Face on Google Cloud, you can get community support by creating a new topic in the <a href="https://discuss.huggingface.co/c/google-cloud/69/l/latest" rel="nofollow">Forum</a> dedicated to Google Cloud usage.</p>  <h2 class="relative group"><a id="train-and-deploy-models-on-google-cloud-with-hugging-face-deep-learning-containers" 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="#train-and-deploy-models-on-google-cloud-with-hugging-face-deep-learning-containers"><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>Train and Deploy Models on Google Cloud with Hugging Face Deep Learning Containers</span></h2> <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-7tem3l">For training, our DLCs are available for PyTorch via 🤗 Transformers. They include support for training on both GPUs and TPUs with libraries such as 🤗 TRL, Sentence Transformers, or 🧨 Diffusers.</p> <p data-svelte-h="svelte-496whm">For inference, we have a general-purpose PyTorch inference DLC, for serving models trained with any of those frameworks mentioned before on both CPU and GPU. There is also the Text Generation Inference (TGI) DLC for high-performance text generation of LLMs on both GPU and TPU. Finally, there is a Text Embeddings Inference (TEI) DLC for high-performance serving of embedding models on both CPU and GPU.</p> <p data-svelte-h="svelte-l6cz0x">The DLCs are hosted in <a href="https://console.cloud.google.com/artifacts/docker/deeplearning-platform-release/us/gcr.io" rel="nofollow">Google Cloud Artifact Registry</a> and can be used from any Google Cloud service such as Google Kubernetes Engine (GKE), Vertex AI, or Cloud Run (in preview).</p> <p data-svelte-h="svelte-rlga4q">Hugging Face DLCs are open source and licensed under Apache 2.0 within the <a href="https://github.com/huggingface/Google-Cloud-Containers" rel="nofollow">Google-Cloud-Containers</a> repository. For premium support, our <a href="https://huggingface.co/support" rel="nofollow">Expert Support Program</a> gives you direct dedicated support from our team.</p> <p data-svelte-h="svelte-1rcb745">You have two options to take advantage of these DLCs as a Google Cloud customer:</p> <ol data-svelte-h="svelte-ca3bc9"><li>To <a href="https://huggingface.co/blog/google-cloud-model-garden" rel="nofollow">get started</a>, you can use our no-code integrations within Vertex AI or GKE.</li> <li>For more advanced scenarios, you can pull the containers from the Google Cloud Artifact Registry directly in your environment. <a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples" rel="nofollow">Here</a> is a list of notebooks examples.</li></ol> <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/index.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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