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Deploy an Embedding Model

  • how-to
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    Use the Capella Model Service to deploy embedding models for vectorizing text.

    An embedding model vectorizes text into numerical vectors that capture their semantic meaning, allowing AI systems to identify similarities between content. You can use embedding models you deploy through the Capella Model Service with Capella AI Services Workflows.

    Prerequisites

    Procedure

    1. From your organization, go to AI Services  Models.

    2. Click Deploy New Model.

    3. Choose an embedding model to deploy:

      1. Click View All Models.

      2. Click Type:All and deselect the LLM, Text to Text option, or use the search bar to find a specific embedding model.

      3. Click the model you want to deploy.

      4. Click Use Selected Model.

    4. Enter a name for the embedding model that you’re deploying.

    5. Choose the AWS region where you want to deploy the model.

    6. Choose the compute and GPU size configuration to run the model.

      The minimum supported compute size available for the model in your chosen region is the default.

    7. (Optional) Apply advanced configuration options:

      If you change or enable any advanced configurations, such as value adds or security features, after deployment, your existing Model Service API keys will stop working, and you must create a new API key. For more information, see Value Adds and Security Features.
      Dimensions

      When available, you can configure your embedding model to generate vectors with more or fewer dimensions by adjusting the Dimensions setting.

      You cannot change this setting after you deploy the embedding model.

      For more information, see Configure Embedding Model Performance.

      Async Processing

      Increase throughput by processing jobs asynchronously when system capacity becomes available. This allows tasks to be queued and handled as resources permit, improving overall efficiency.

      For more information, see Configure Embedding Model Performance.

    8. Click Deploy Model.

    Next Steps

    The Models page opens with your model in a deploying state. Once the model has finished deploying, you can view the model details and manage the model by expanding its listing on the Models page.

    To create API keys for your deployed model, see Generate Model Service API Keys.

    You can also: