Try it: Test model capabilities using demo playgrounds in Model Garden

Model Garden hosts public demo playgrounds for supported models. The playgrounds are powered by predeployed Vertex AI online prediction endpoints.

When you open the model card for a supported model, a Try out panel is embedded in the card. You can quickly test the model's capabilities by sending a text prompt in the Try out panel. The Try out panel also lets you set some of the most common parameters such as temperature and number of output tokens.

Supported models

The following models have demo playgrounds available.

Provider	Models
Google	Gemma 2 2B it (instruction tuned) Gemma 2 9B it (instruction tuned) Gemma 2 27B it (instruction tuned) Gemma 2B Gemma 2B it (instruction tuned) Gemma 7B Gemma 7B it (instruction tuned)
Meta	Llama 3 8B Instruct Llama 3 70B Instruct Llama 2 7B Llama 2 7B Chat Llama 2 13B Chat Llama 2 70B Chat (Int8) Code Llama 7B Python
TII	Falcon 7B
Mistral AI	Mixtral 8x7B

Before you begin

This tutorial requires you to set up a Google Cloud project and enable the Vertex AI API.

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.

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.

Go to project selector

Verify that billing is enabled for your Google Cloud project.

Enable the Vertex AI API.

Enable the API

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

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.

Go to project selector

Verify that billing is enabled for your Google Cloud project.

Enable the Vertex AI API.

Enable the API

Try out Gemma 2

In this quickstart, you try out the Gemma-2b-it model. Note that -it stands for instruction-tuned.

1. In the Google Cloud console, go to the Gemma 2 model card.

   Go to Gemma 2

2. In the Try out panel:

   1. For Region, accept the default or choose your region.
   2. For Endpoint, select Demo playground (Free)2b-it.
   3. In the Prompt box, enter Why is the sky blue?.

   4. Expand the Advanced options section and view the default parameters.

      

3. Click Submit. The output appears below the Submit button.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used on this page, follow these steps.

Delete the project

The easiest way to eliminate billing is to delete the project that you created for the tutorial.

To delete the project:

Caution: Deleting a project has the following effects:

• Everything in the project is deleted. If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.
• Custom project IDs are lost. When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an appspot.com URL, delete selected resources inside the project instead of deleting the whole project.

If you plan to explore multiple architectures, tutorials, or quickstarts, reusing projects can help you avoid exceeding project quota limits.

1. In the Google Cloud console, go to the Manage resources page.

   Go to Manage resources

2. In the project list, select the project that you want to delete, and then click Delete.
3. In the dialog, type the project ID, and then click Shut down to delete the project.

What's next

See an overview of Model Garden.