Vertex AI Model Registry 是中央存放區,可用於管理機器學習模型的生命週期。Model Registry 會顯示模型總覽,方便您更妥善地整理、追蹤及訓練新版本。有想部署的模型版本時,可以直接從登錄檔將模型指派給端點,也可以使用別名將模型部署至端點。
Vertex AI Model Registry 支援自訂模型和所有 AutoML 資料類型,包括表格、圖片和影片。模型登錄服務也支援 BigQuery ML 模型。如果您有在 BigQuery ML 中訓練的模型,可以直接向 Model Registry 註冊,不必從 BigQuery ML 匯出,也不必匯入 Model Registry。
您可以在模型版本詳細資料頁面中評估模型、部署至端點、設定批次推論,以及查看特定模型詳細資料。Vertex AI Model Registry 提供簡單易用的介面,可管理及部署最佳模型至實際工作環境。
常見工作流程
在 Model Registry 中工作時,有許多有效的工作流程。
如要開始使用,建議您先按照這些指南瞭解 Model Registry 的功能,以及模型訓練歷程的各個階段。
[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間:2025-09-04 (世界標準時間)。"],[],[],null,["# Introduction to Vertex AI Model Registry\n\n| To see an example of getting started with Vertex AI Model Registry,\n| run the \"Get started with Vertex AI Model Registry\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_registry/get_started_with_model_registry.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fmodel_registry%2Fget_started_with_model_registry.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fmodel_registry%2Fget_started_with_model_registry.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_registry/get_started_with_model_registry.ipynb)\n\nThe Vertex AI Model Registry is a central repository where you can manage\nthe lifecycle of your ML models. From the Model Registry,\nyou have an overview of your models so you can better organize, track,\nand train new versions. When you have a model version you would like to deploy,\nyou can assign it to an endpoint directly from the registry,\nor using aliases, deploy models to an endpoint.\n\nThe Vertex AI Model Registry supports custom models and all\nAutoML data types - tabular, image, and video. The\nModel Registry\ncan also support BigQuery ML models. If you have models trained in\nBigQuery ML, you can register them with the\nModel Registry without needing to export them from\nBigQuery ML or import them into the Model Registry.\n\nFrom the model version details page you can evaluate, deploy to an endpoint,\nset up batch inference, and view specific model details. The Vertex AI Model Registry\nprovides a straightforward and streamlined interface to manage and deploy your\nbest models to production.\n\nCommon workflow\n---------------\n\nThere are many valid workflows for working in the Model Registry.\nTo get started, you might want to follow these guidelines to understand what you can\ndo in the Model Registry and at what stage in your model-training journey.\n\n- Import models to the Model Registry.\n- Create new models, assign a model version the default alias, ready for production.\n- Add other aliases, or labels to help you manage and organize your models and model versions.\n- Deploy your models to an endpoint for online inference.\n- Run batch inference, and start your model evaluation pipeline.\n- View your model details and view performance metrics from the model details page.\n\nTo learn more about how to integrate your BigQuery ML models with\nVertex AI, see the\n[BigQuery ML documentation.](/bigquery-ml/docs/managing-models-vertex)\n\nSearch and discover models using Dataplex Universal Catalog\n-----------------------------------------------------------\n\nDataplex Universal Catalog is a platform for storing, managing, and accessing your\nmetadata. Dataplex Universal Catalog provides a way to search\nfor your Vertex AI models across projects and regions.\n\nFor more information, see [About data catalog management in\nDataplex Universal Catalog](/dataplex/docs/catalog-overview).\n\nWhat's next\n-----------\n\nTo get started using Vertex AI Model Registry, see:\n\n- [Import models to Vertex AI](/vertex-ai/docs/model-registry/import-model)\n- [Model versioning with Model Registry](/vertex-ai/docs/model-registry/versioning)\n- [How to use model version aliases](/vertex-ai/docs/model-registry/model-alias)\n- [BigQuery ML and Model Registry](/vertex-ai/docs/model-registry/model-registry-bqml)\n- [Copy a model in Vertex AI Model Registry](/vertex-ai/docs/model-registry/copy-model)"]]