Criar uma instância de VM de aprendizado profundo no Cloud Marketplace
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Nesta página, mostramos como criar uma instância do Deep Learning VM Images
pelo Cloud Marketplace no
consoleGoogle Cloud sem usar a linha de comando.
Antes de começar
Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
Se estiver usando GPUs com sua VM de aprendizado profundo, verifique a
página de cotas
para garantir que você tenha
GPUs suficientes disponíveis no seu projeto. Se as GPUs não estiverem listadas
nessa página ou se você precisar de cotas adicionais,
solicite um
aumento de cota.
Criar uma instância
Acesse a página de VM de aprendizado profundo do Cloud Marketplace no
console Google Cloud .
Em GPUs, selecione o Tipo de GPU e o Número de GPUs.
Se não quiser usar GPUs,
clique no botão Excluir GPU
e pule para a etapa 7. Saiba mais sobre GPUs.
Se você estiver usando GPUs, precisará de um driver NVIDIA.
É possível instalar o driver
você mesmo ou selecionar Instalar driver de GPU NVIDIA automaticamente
na primeira inicialização.
Você tem a opção de selecionar Ativar o acesso ao JupyterLab por URL
em vez de SSH (Beta). A ativação desse recurso Beta permite
acessar sua instância do JupyterLab
usando um URL. Qualquer pessoa que tenha o papel Editor ou Proprietário no seu projeto do Google Cloud poderá acessar esse URL.
Atualmente, esse recurso funciona
apenas nos Estados Unidos, na União Europeia e na Ásia.
Selecione um tipo de disco de inicialização e um tamanho de disco de inicialização.
Selecione as configurações de rede que você quer.
Clique em Implantar.
Se você optar por instalar os drivers da NVIDIA, aguarde de três a cinco minutos para concluir
a instalação.
Depois que a VM for implantada, a página será atualizada com instruções
para acessar a instância.
A seguir
Para instruções sobre como se conectar à nova instância de VM de aprendizado profundo
pelo console ou pela linha de comando do Google Cloud , consulte Como se conectar a
instâncias. O nome da instância é o Nome da implantação que você especificou com -vm anexado.
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-08-17 UTC."],[[["\u003cp\u003eThis guide outlines how to create a Deep Learning VM instance directly from the Google Cloud Marketplace within the console, eliminating the need for command-line operations.\u003c/p\u003e\n"],["\u003cp\u003eBefore creating the instance, you must select a specific Deep Learning VM image based on your preferred framework and processor type, and check that enough GPU quota is available if you are planning to use GPUs.\u003c/p\u003e\n"],["\u003cp\u003eThe instance creation process involves selecting a deployment name, zone, machine type, optional GPU settings, and machine learning framework, then it includes selecting a boot disk and networking settings before deployment.\u003c/p\u003e\n"],["\u003cp\u003eIf you are planning to use GPUs, you will need to install the NVIDIA drivers, which can be done automatically on the first startup, and you also have the choice of enabling JupyterLab access via URL.\u003c/p\u003e\n"],["\u003cp\u003eAfter deployment, you will be provided instructions to access the instance, and the instance name is created by appending \u003ccode\u003e-vm\u003c/code\u003e to the deployment name that was chosen during setup.\u003c/p\u003e\n"]]],[],null,["# Create a Deep Learning VM instance from Cloud Marketplace\n\nThis page shows you how to create a Deep Learning VM Images instance\nfrom Cloud Marketplace within the\nGoogle Cloud console without using the command line.\n\nBefore you begin\n----------------\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n1. [Choose a specific Deep Learning VM\n image to use](/deep-learning-vm/docs/images). Your choice depends on your preferred framework and processor type.\n2. If you are using GPUs with your Deep Learning VM, check the [quotas page](https://console.cloud.google.com/quotas) to ensure that you have enough GPUs available in your project. If GPUs are not listed on the quotas page or you require additional GPU quota, [request a\n quota increase](/compute/quotas#requesting_additional_quota).\n\nCreating an instance\n--------------------\n\n1. Go to the Deep Learning VM Cloud Marketplace page in\n the Google Cloud console.\n\n [Go to the Deep Learning VM Cloud Marketplace page](https://console.cloud.google.com/marketplace/details/click-to-deploy-images/deeplearning)\n2. Click **Get started**.\n\n3. Enter a **Deployment name** , which will be the root of your VM name.\n Compute Engine appends `-vm` to this name when naming your instance.\n\n4. Select a **Zone**.\n\n5. Under **Machine type** , select the specifications that you\n want for your VM.\n [Learn more about machine types.](/compute/docs/machine-types)\n\n6. Under **GPUs** , select the **GPU type** and **Number of GPUs** .\n If you don't want to use GPUs,\n click the **Delete GPU** button\n and skip to step 7. [Learn more about GPUs.](/gpu)\n\n 1. Select a **GPU type** . Not all GPU types are available in all zones. [Find a combination that is supported.](/compute/docs/gpus)\n 2. Select the **Number of GPUs** . Each GPU supports different numbers of GPUs. [Find a combination that is supported.](/compute/docs/gpus)\n7. Select a machine learning **Framework**.\n\n8. If you're using GPUs, an NVIDIA driver is required.\n You can install the driver\n yourself, or select **Install NVIDIA GPU driver automatically\n on first startup**.\n\n9. You have the option to select **Enable access to JupyterLab via URL\n instead of SSH (Beta)**. Enabling this Beta feature lets you\n access your JupyterLab\n instance using a URL. Anyone who is in the Editor or Owner role in your\n Google Cloud project can access this URL.\n Currently, this feature only works in\n the United States, the European Union, and Asia.\n\n10. Select a boot disk type and boot disk size.\n\n11. Select the networking settings that you want.\n\n12. Click **Deploy**.\n\nIf you choose to install NVIDIA drivers, allow 3-5 minutes for installation\nto complete.\n\nAfter the VM is deployed, the page updates with instructions for\naccessing the instance.\n\nWhat's next\n-----------\n\nFor instructions on connecting to your new Deep Learning VM instance\nthrough the Google Cloud console or command line, read [Connecting to\nInstances](/compute/docs/instances/connecting-to-instance). Your instance name\nis the **Deployment name** you specified with `-vm` appended."]]
