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Configure Databricks Model Serving to access foundation models and custom models through Braintrust.

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Authentication

Choose between two authentication methods:
  • Personal Access Token (PAT): Use a Databricks personal access token for authentication
  • Service Principal OAuth: Use OAuth with a service principal for authentication

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Configuration

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Models

Databricks provides access to several foundation models through Model Serving.

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Foundation models

  • Meta Llama 3.1 70B Instruct
  • Meta Llama 3.1 8B Instruct
  • Mistral 7B Instruct
  • Mixtral 8x7B Instruct
  • MPT-7B Instruct

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Custom models

Deploy your own fine-tuned models through Databricks Model Serving.

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Setup requirements

  1. Databricks Workspace: Ensure you have access to a Databricks workspace
  2. Model Serving: Enable Model Serving in your workspace
  3. Authentication: Set up either PAT or service principal authentication
  4. Model Endpoints: Deploy the models you want to use as serving endpoints

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Endpoint configuration

Configure the following for model endpoints in Databricks.
  1. Serving Endpoint Name: Use this as the model name in Braintrust
  2. Endpoint URL: Automatically constructed from your workspace URL
  3. Authentication: Uses the configured authentication method

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Additional resources