Given a successful build, you can deploy your model as a batch application.
This deployment type allows you to run batch inference executions in the system, and handle data files from an online cloud storage provider.
|Model ID [Required]||The Model ID, as displayed on the model header.|
|Build ID [Required]||The Qwak-assigned build ID.|
|Initial number of pods||The number of k8s pods to be used by the deployment.|
Each pod handles one or more files/tasks.
|CPU fraction||The CPU fraction allocated to each pod. The CPU resource is measured in CPU units. One CPU, in Qwak, is equivalent to:|
1 AWS vCPU
1 GCP Core
1 Azure vCore
1 Hyperthread on a bare-metal Intel processor with Hyperthreading
|Memory||The RAM memory (in MB) to allocate to each pod.||512|
|IAM role ARN||The user-provided AWS custom IAM role.||None|
|GPU Type||The GPU Type to use in the model deployment. Supported options are, NVIDIA K80, NVIDIA Tesla V100, NVIDIA T4 and NVIDIA A10.||None|
|GPU Amount||The number of GPUs available for the model deployment.|
Varies based on the selected GPU type.
|Based on GPU Type|
To deploy a batch model from the UI:
- In the left navigation bar in the Qwak UI, select Projects.
- Select a project and then select a model.
- Select the Builds tab. Find a build to deploy and click the deployment toggle. The Deploy dialog box appears.
- Select Batch and then select Next.
A deployment request is sent and the loading spinner is displayed for the selected build.
To deploy a model in batch mode from the CLI, populate the following command template:
qwak models deploy batch \ --model-id <model-id> \ --build-id <build-id> \ --pods <pods-count> \ --cpus <cpus-fraction> \ --memory <memory-size>
For example, for the model built in the Getting Started with Qwak section, the deployment command is:
qwak models deploy batch \ --model-id churn_model \ --build-id 7121b796-5027-11ec-b97c-367dda8b746f \ --pods 4 \ --cpus 3 \ --memory 1024
Updated 3 days ago