Before you begin

Before you can use AutoML Translation, you must enable it for your project. Open the AutoML Translation UI and select your project from the drop-down list in the upper right of the title bar. The application walks you through the necessary steps, which are also described below.

Set up your project

  1. Sign in to your Google Account.

    If you don't already have one, sign up for a new account.

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

    Go to the project selector page

  3. Make sure that billing is enabled for your Cloud project. Learn how to confirm that billing is enabled for your project.

  4. Enable the AutoML and Cloud Storage APIs.

    Enable the APIs

  5. Install the gcloud command line tool.
  6. Follow the instructions to create a service account and download a key file for that account.
  7. Set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path to the service account key file that you downloaded when you created the service account.
    export GOOGLE_APPLICATION_CREDENTIALS=key-file
  8. Set the PROJECT_ID environment variable to your Project ID.
    export PROJECT_ID=your-project-id
    The AutoML API calls and resource names include your Project ID in them. The PROJECT_ID environment variable provides a convenient way to specify the ID.
  9. If you are an owner for your project, add your service account to the AutoML Editor IAM role, replacing service-account-name with the name of your new service account. For example, service-account1@myproject.iam.gserviceaccount.com.
    gcloud auth login
    gcloud projects add-iam-policy-binding $PROJECT_ID \
       --member="serviceAccount:service-account-name" \
       --role="roles/automl.editor"
    
  10. Otherwise (if you are not a project owner), ask a project owner to add both your user ID and your service account to the AutoML Editor IAM role.

Create a Cloud Storage bucket

Create a Google Cloud Storage bucket to store the sentence pairs that you will use to train your custom model. The bucket name must be in the format: project-id-vcm. The following command creates a storage bucket in the us-central1 region named project-id-vcm.

gsutil mb -p project-id -c regional -l us-central1 gs://project-id-vcm/
We recommend the following file structure for your Cloud Storage files: gs://project-id-vcm/dataset-name/documents/document-name.txt