Deployments
A guide to deploying and accessing your AutoML models
Overview
After training an AutoML model, you can create a Deployment
to submit requests to the model via an API endpoint. A deployment is a version of your model that is ready for inference requests. A deployment points to a Hive Data project that lets you submit requests to the model in the same way that you would interact with any Hive pre-trained model.
Create a Deployment
To create a deployment, go to a detail page for the model you would like to deploy and click the Create Deployment
button in the top right.
All deployments for a model can be seen under the deployments tab.
Clicking the name of a deployment opens the corresponding Hive Data project, allowing you to access API keys and view information about all submitted inference requests.
To begin using your model, click on the API Keys
button on the top right of the Hive Data project page to copy your API Key. For instructions on how to submit a task via API, either synchronously or asynchronously, see our API Reference documentation.
Update Deployment
If you'd like to move a deployment from one training to another, you can update your deployment. This option is useful in the case that you want to continue to use the same API key, but you want to switch version of the model you're using. To do this, open the Deployments
tab and click on the Update
button located to the right of the Undeploy
button (see the image below). After clicking on the button, you'll just need to choose which model version you want to update to.
Video Inference
If you would like to submit videos to an Image Classification model, you will need to check the Use Video Inference
checkbox on your Create Deployment
form. Deployments without this option will only be able to support images.
Updated 7 months ago