From PVC (CLI)
If you have already pre-loaded a model onto a Persistant Volume Claim (PVC), you can add the model to HPE Machine Learning Inferencing Software by following the steps below.
Before You Start #
- Create a PVC
- Obtain the model’s path within the PVC
- Review any necessary resources specific to the model you have pre-loaded:
PVC Syntax & URL Options #
Review the following PVC syntax and URL options to ensure you have the correct information for adding your model.
| Option | Description | Example | Default |
|---|---|---|---|
| PVC Name | Name of the Persistent Volume Claim (PVC) to be mounted | pvc://my-model-pvc | Required, no default |
| Path | Optional path within the PVC to be mounted | pvc://my-model-pvc/models | If not specified, the entire PVC is mounted |
| ContainerPath | Directory in container where the PVC is mounted | pvc://my-model-pvc?containerPath=/mnt/models | /mnt/models |
| readOnly | Whether the volume is read-only | pvc://my-model-pvc?readOnly | If not specified, the volume is read-write |
PVC Name
<my-model-pvc>) must already exist in the Kubernetes namespace where the packaged model will be deployed.How to Add a Packaged Model From PVC #
-
Sign in via the CLI.
aioli user login <YOUR_USERNAME> -
Create a new model with the following command:
aioli model create <MODEL_NAME> \ --modelformat custom \ --image <USER_NAME>/<MODEL_NAME>:<TAG> \ --url pvc://<PVC_NAME>/<OPTIONAL_PATH>?containerPath=<DIR_IN_CONTAINER> \ --description <DESCRIPTION> \ --arg=--model_dir=<PATH_WHERE_MODEL_IS_STORED>- For more information on the
aioli model createcommand, see the CLI command reference. - For information on setting environment variables and arguments, see the Advanced Configuration reference article.
- For more information on the