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pub struct DescribeModelOutput {
    pub containers: Option<Vec<ContainerDefinition>>,
    pub creation_time: f64,
    pub enable_network_isolation: Option<bool>,
    pub execution_role_arn: String,
    pub inference_execution_config: Option<InferenceExecutionConfig>,
    pub model_arn: String,
    pub model_name: String,
    pub primary_container: Option<ContainerDefinition>,
    pub vpc_config: Option<VpcConfig>,
}

Fields

containers: Option<Vec<ContainerDefinition>>

The containers in the inference pipeline.

creation_time: f64

A timestamp that shows when the model was created.

enable_network_isolation: Option<bool>

If True, no inbound or outbound network calls can be made to or from the model container.

execution_role_arn: String

The Amazon Resource Name (ARN) of the IAM role that you specified for the model.

inference_execution_config: Option<InferenceExecutionConfig>

Specifies details of how containers in a multi-container endpoint are called.

model_arn: String

The Amazon Resource Name (ARN) of the model.

model_name: String

Name of the Amazon SageMaker model.

primary_container: Option<ContainerDefinition>

The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.

vpc_config: Option<VpcConfig>

A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud

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