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Vertex AI Model Garden Deploy

Deploy and undeploy open-source and custom models to Vertex AI endpoints.

775|303|Updated May 27, 2021
Search Tags:#endpoints#model deployment#gemma#vertex ai#model garden#custom weights
One-click install
npx skills add https://github.com/GoogleCloudPlatform/vertex-ai-samples --skill vertex-ai-model-garden-deploy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Vertex AI Model Garden Deploy
Source: https://github.com/GoogleCloudPlatform/vertex-ai-samples/tree/main/skills/vertex-deploy
Command: npx skills add https://github.com/GoogleCloudPlatform/vertex-ai-samples --skill vertex-ai-model-garden-deploy

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill simplifies the process of deploying open-source models from Vertex AI Model Garden to Vertex AI endpoints, and helps in cleaning up these resources afterward.

Core Features & Use Cases

  • Model Deployment: Deploy pre-trained open models or custom weights to Vertex AI endpoints.
  • Resource Management: Provides guidance on undeploying models and deleting endpoints to manage costs.
  • Use Case: A data scientist wants to deploy the Gemma 3 model to an endpoint for real-time inference. This skill guides them through the deployment, verification, and eventual cleanup process.

Quick Start

Use the Vertex AI Model Garden Deploy skill to deploy the google/gemma3@gemma-3-27b-it model to a Vertex AI endpoint.

Frequently Asked Questions about Vertex AI Model Garden Deploy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy an open-source model to a Vertex AI endpoint?▼

To deploy an open-source model to a Vertex AI endpoint, you configure the target machine type and accelerators, then trigger an asynchronous deployment process that provisions the endpoint for real-time inference.

Can I deploy custom weights to Vertex AI Model Garden endpoints?▼

Yes, you can deploy custom weights to Vertex AI endpoints. The deployment process supports both pre-trained open-source models from Model Garden and your own custom-weighted models for serving.

How do I check the status of my asynchronous Vertex AI model deployment?▼

You can check the status of your asynchronous Vertex AI model deployment using the provided status checking functionality, which monitors the endpoint provisioning and model deployment lifecycle.

What is the best way to undeploy models and delete Vertex AI endpoints to manage costs?▼

The best way to manage costs is to use the resource cleanup functionality to undeploy models and delete Vertex AI endpoints. This ensures that you remove deployed models and infrastructure when they are no longer needed.

Does this deployment process support discovering specific models like Gemma 3?▼

Yes, the deployment process supports model discovery within Vertex AI Model Garden. You can discover and deploy specific open models like the Gemma 3 model directly to your configured Vertex AI endpoints.

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