Install the CLI

bash -c "$(curl -sS"

You must have Docker installed to run Cortex locally or to create a cluster on AWS.

Deploy an example

# clone the Cortex repository
git clone -b 0.20
# navigate to the Pytorch text generator example
cd cortex/examples/pytorch/text-generator
# deploy the model as a realtime api
cortex deploy
# view the status of the api
cortex get --watch
# stream logs from the api
cortex logs text-generator
# get the api's endpoint
cortex get text-generator
# classify a sample
curl <API endpoint> \
-X POST -H "Content-Type: application/json" \
-d '{"text": "machine learning is"}' \
# delete the api
cortex delete text-generator

Running at scale on AWS

Run the command below to create a cluster with basic configuration, or see cluster configuration to learn how you can customize your cluster with cluster.yaml.

See EC2 instances for an overview of several EC2 instance types. To use GPU nodes, you may need to subscribe to the EKS-optimized AMI with GPU Support and file an AWS support ticket to increase the limit for your desired instance type.

# create a Cortex cluster on your AWS account
cortex cluster up
# set the default CLI environment (optional)
cortex env default aws

You can now run the same commands shown above to deploy the text generator to AWS (if you didn't set the default CLI environment, add --env aws to the cortex commands).

Next steps

  • Try the tutorial to learn more about how to use Cortex.

  • Deploy one of our examples.

  • See our exporting guide for how to export your model to use in an API.

  • See uninstall if you'd like to spin down your cluster.