Create Custom Model Deployment
| bedrock_create_custom_model_deployment | R Documentation |
Deploys a custom model for on-demand inference in Amazon Bedrock¶
Description¶
Deploys a custom model for on-demand inference in Amazon Bedrock. After
you deploy your custom model, you use the deployment's Amazon Resource
Name (ARN) as the modelId parameter when you submit prompts and
generate responses with model inference.
For more information about setting up on-demand inference for custom models, see Set up inference for a custom model.
The following actions are related to the
create_custom_model_deployment operation:
-
get_custom_model_deployment -
list_custom_model_deployments -
delete_custom_model_deployment
Usage¶
bedrock_create_custom_model_deployment(modelDeploymentName, modelArn,
description, tags, clientRequestToken)
Arguments¶
modelDeploymentName |
[required] The name for the custom model deployment. The name must be unique within your Amazon Web Services account and Region. |
modelArn |
[required] The Amazon Resource Name (ARN) of the custom model to
deploy for on-demand inference. The custom model must be in the
|
description |
A description for the custom model deployment to help you identify its purpose. |
tags |
Tags to assign to the custom model deployment. You can use tags to organize and track your Amazon Web Services resources for cost allocation and management purposes. |
clientRequestToken |
A unique, case-sensitive identifier to ensure that the operation completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency. |
Value¶
A list with the following syntax:
list(
customModelDeploymentArn = "string"
)
Request syntax¶
svc$create_custom_model_deployment(
modelDeploymentName = "string",
modelArn = "string",
description = "string",
tags = list(
list(
key = "string",
value = "string"
)
),
clientRequestToken = "string"
)