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Model Serve resource quick reference

Model Serve
resource quick reference

The following list contains the syntax and a brief description of the actions you can perform with the

Model Serve

resources:

Get descriptions of all quick start models: To get a list of the names and descriptions of all of the quick start models, use the following URI:
/mlops/api/v1/modelhub/models
Monitor all quick start models: To get the statuses of and information about all of the quick start models, use the following URI:
/mlops/api/v1/modelhub/monitor
Get information about a quick start model: To get the status of and information about a single quick start model, use the following URI:
/mlops/api/v1/modelhub/preBuiltModel?name=<model name>

Use
TEXT_TRANSLATION
or
IMAGE_CLASSIFICATION
as the model name.
Get the code template file: To get the code template file that you need to define a machine learning model, use the following URI:
/mlops/api/v1/model/template/custom
Upload a model file: When you upload a model file, first generate a model file ID and then use the ID to upload the file.
To generate a model file ID, use the following URI:
/mlops/api/v1/model/upload/generateId

To upload or update a model file, use the following URI:
/mlops/api/v1/model/upload/<model file ID>
Register a machine learning model: Register a machine learning model after you upload the model file that defines the machine learning algorithm.

To register a machine learning model, use the following URI:
/frs/v1/Projects('<model ID>')/Documents
Edit a machine learning model: To edit a registered machine learning model, use the following URI:
/frs/v1/Documents('<ID>')
Download a model file: To download the model file from a registered machine learning model, use the following URI:
/mlops/api/v1/model/download/<ID>
Create a model deployment: To create a model deployment based on a registered machine learning model, use the following URI:
/frs/v1/Projects('<deployment ID>')/Documents
Edit a model deployment: To edit a model deployment, use the following URI:
/frs/v1/Documents('<deployment ID>')
Monitor deployments: To monitor the status of all model deployments in your organization, use the following URI:
/mlops/api/v1/deployment/monitor

To monitor the status of one model deployment, use the following URI:
/mlops/api/v1/deployment/monitor/<deployment ID>
Control a quick start model or model deployment: You can start a quick start model or model deployment to make it available for predictions, restart it while it's running, and stop it to release the resources.
To start a deployment, use the following URI:
/mlops/api/v1/deployment/control/<deployment ID>/start

To restart a deployment, use the following URI:
/mlops/api/v1/deployment/control/<deployment ID>/restart

To stop a deployment, use the following URI:
/mlops/api/v1/deployment/control/<deployment ID>/stop
Generate predictions: To generate predictions from an available quick start model or model deployment, use the following URI:
/mlops/api/v1/deployment/request/<deployment ID>
Delete assets: To delete a machine learning model or model deployment, use the following URI:
/frs/api/v1/Documents('<ID>')