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Deploy trained models

Serverless

Elastic Cloud Serverless projects are autoscaled environments, fully managed by Elastic and available on Elastic Cloud.

Availability

  • Generally available

    This functionality is generally available and ready for production usage.

Serverless interfaces and procedures might differ from classic Elastic Stack deployments.

Stack

The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats.

Availability

  • Generally available

    This functionality is generally available and ready for production usage.

Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments.

This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes.

If you want to perform natural language processing tasks in your cluster, you must deploy an appropriate trained model. There is tooling support in Eland and Kibana to help you prepare and manage models.

  1. Select a trained model.
  2. Import the trained model and vocabulary.
  3. Deploy the model in your cluster.
  4. Try it out.