aws.bedrock.CustomModel
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Example Usage
import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";
const example = aws.bedrockfoundation.getModel({
    modelId: "amazon.titan-text-express-v1",
});
const exampleCustomModel = new aws.bedrock.CustomModel("example", {
    customModelName: "example-model",
    jobName: "example-job-1",
    baseModelIdentifier: example.then(example => example.modelArn),
    roleArn: exampleAwsIamRole.arn,
    hyperparameters: {
        epochCount: "1",
        batchSize: "1",
        learningRate: "0.005",
        learningRateWarmupSteps: "0",
    },
    outputDataConfig: {
        s3Uri: `s3://${output.id}/data/`,
    },
    trainingDataConfig: {
        s3Uri: `s3://${training.id}/data/train.jsonl`,
    },
});
import pulumi
import pulumi_aws as aws
example = aws.bedrockfoundation.get_model(model_id="amazon.titan-text-express-v1")
example_custom_model = aws.bedrock.CustomModel("example",
    custom_model_name="example-model",
    job_name="example-job-1",
    base_model_identifier=example.model_arn,
    role_arn=example_aws_iam_role["arn"],
    hyperparameters={
        "epochCount": "1",
        "batchSize": "1",
        "learningRate": "0.005",
        "learningRateWarmupSteps": "0",
    },
    output_data_config={
        "s3_uri": f"s3://{output['id']}/data/",
    },
    training_data_config={
        "s3_uri": f"s3://{training['id']}/data/train.jsonl",
    })
package main
import (
	"fmt"
	"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/bedrock"
	"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/bedrockfoundation"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		example, err := bedrockfoundation.GetModel(ctx, &bedrockfoundation.GetModelArgs{
			ModelId: "amazon.titan-text-express-v1",
		}, nil)
		if err != nil {
			return err
		}
		_, err = bedrock.NewCustomModel(ctx, "example", &bedrock.CustomModelArgs{
			CustomModelName:     pulumi.String("example-model"),
			JobName:             pulumi.String("example-job-1"),
			BaseModelIdentifier: pulumi.String(example.ModelArn),
			RoleArn:             pulumi.Any(exampleAwsIamRole.Arn),
			Hyperparameters: pulumi.StringMap{
				"epochCount":              pulumi.String("1"),
				"batchSize":               pulumi.String("1"),
				"learningRate":            pulumi.String("0.005"),
				"learningRateWarmupSteps": pulumi.String("0"),
			},
			OutputDataConfig: &bedrock.CustomModelOutputDataConfigArgs{
				S3Uri: pulumi.Sprintf("s3://%v/data/", output.Id),
			},
			TrainingDataConfig: &bedrock.CustomModelTrainingDataConfigArgs{
				S3Uri: pulumi.Sprintf("s3://%v/data/train.jsonl", training.Id),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;
return await Deployment.RunAsync(() => 
{
    var example = Aws.BedrockFoundation.GetModel.Invoke(new()
    {
        ModelId = "amazon.titan-text-express-v1",
    });
    var exampleCustomModel = new Aws.Bedrock.CustomModel("example", new()
    {
        CustomModelName = "example-model",
        JobName = "example-job-1",
        BaseModelIdentifier = example.Apply(getModelResult => getModelResult.ModelArn),
        RoleArn = exampleAwsIamRole.Arn,
        Hyperparameters = 
        {
            { "epochCount", "1" },
            { "batchSize", "1" },
            { "learningRate", "0.005" },
            { "learningRateWarmupSteps", "0" },
        },
        OutputDataConfig = new Aws.Bedrock.Inputs.CustomModelOutputDataConfigArgs
        {
            S3Uri = $"s3://{output.Id}/data/",
        },
        TrainingDataConfig = new Aws.Bedrock.Inputs.CustomModelTrainingDataConfigArgs
        {
            S3Uri = $"s3://{training.Id}/data/train.jsonl",
        },
    });
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.bedrockfoundation.BedrockfoundationFunctions;
import com.pulumi.aws.bedrockfoundation.inputs.GetModelArgs;
import com.pulumi.aws.bedrock.CustomModel;
import com.pulumi.aws.bedrock.CustomModelArgs;
import com.pulumi.aws.bedrock.inputs.CustomModelOutputDataConfigArgs;
import com.pulumi.aws.bedrock.inputs.CustomModelTrainingDataConfigArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }
    public static void stack(Context ctx) {
        final var example = BedrockfoundationFunctions.getModel(GetModelArgs.builder()
            .modelId("amazon.titan-text-express-v1")
            .build());
        var exampleCustomModel = new CustomModel("exampleCustomModel", CustomModelArgs.builder()
            .customModelName("example-model")
            .jobName("example-job-1")
            .baseModelIdentifier(example.applyValue(getModelResult -> getModelResult.modelArn()))
            .roleArn(exampleAwsIamRole.arn())
            .hyperparameters(Map.ofEntries(
                Map.entry("epochCount", "1"),
                Map.entry("batchSize", "1"),
                Map.entry("learningRate", "0.005"),
                Map.entry("learningRateWarmupSteps", "0")
            ))
            .outputDataConfig(CustomModelOutputDataConfigArgs.builder()
                .s3Uri(String.format("s3://%s/data/", output.id()))
                .build())
            .trainingDataConfig(CustomModelTrainingDataConfigArgs.builder()
                .s3Uri(String.format("s3://%s/data/train.jsonl", training.id()))
                .build())
            .build());
    }
}
resources:
  exampleCustomModel:
    type: aws:bedrock:CustomModel
    name: example
    properties:
      customModelName: example-model
      jobName: example-job-1
      baseModelIdentifier: ${example.modelArn}
      roleArn: ${exampleAwsIamRole.arn}
      hyperparameters:
        epochCount: '1'
        batchSize: '1'
        learningRate: '0.005'
        learningRateWarmupSteps: '0'
      outputDataConfig:
        s3Uri: s3://${output.id}/data/
      trainingDataConfig:
        s3Uri: s3://${training.id}/data/train.jsonl
variables:
  example:
    fn::invoke:
      function: aws:bedrockfoundation:getModel
      arguments:
        modelId: amazon.titan-text-express-v1
Create CustomModel Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new CustomModel(name: string, args: CustomModelArgs, opts?: CustomResourceOptions);@overload
def CustomModel(resource_name: str,
                args: CustomModelArgs,
                opts: Optional[ResourceOptions] = None)
@overload
def CustomModel(resource_name: str,
                opts: Optional[ResourceOptions] = None,
                job_name: Optional[str] = None,
                role_arn: Optional[str] = None,
                custom_model_name: Optional[str] = None,
                base_model_identifier: Optional[str] = None,
                hyperparameters: Optional[Mapping[str, str]] = None,
                output_data_config: Optional[CustomModelOutputDataConfigArgs] = None,
                customization_type: Optional[str] = None,
                custom_model_kms_key_id: Optional[str] = None,
                tags: Optional[Mapping[str, str]] = None,
                timeouts: Optional[CustomModelTimeoutsArgs] = None,
                training_data_config: Optional[CustomModelTrainingDataConfigArgs] = None,
                validation_data_config: Optional[CustomModelValidationDataConfigArgs] = None,
                vpc_config: Optional[CustomModelVpcConfigArgs] = None)func NewCustomModel(ctx *Context, name string, args CustomModelArgs, opts ...ResourceOption) (*CustomModel, error)public CustomModel(string name, CustomModelArgs args, CustomResourceOptions? opts = null)
public CustomModel(String name, CustomModelArgs args)
public CustomModel(String name, CustomModelArgs args, CustomResourceOptions options)
type: aws:bedrock:CustomModel
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args CustomModelArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args CustomModelArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args CustomModelArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args CustomModelArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args CustomModelArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var customModelResource = new Aws.Bedrock.CustomModel("customModelResource", new()
{
    JobName = "string",
    RoleArn = "string",
    CustomModelName = "string",
    BaseModelIdentifier = "string",
    Hyperparameters = 
    {
        { "string", "string" },
    },
    OutputDataConfig = new Aws.Bedrock.Inputs.CustomModelOutputDataConfigArgs
    {
        S3Uri = "string",
    },
    CustomizationType = "string",
    CustomModelKmsKeyId = "string",
    Tags = 
    {
        { "string", "string" },
    },
    Timeouts = new Aws.Bedrock.Inputs.CustomModelTimeoutsArgs
    {
        Create = "string",
        Delete = "string",
    },
    TrainingDataConfig = new Aws.Bedrock.Inputs.CustomModelTrainingDataConfigArgs
    {
        S3Uri = "string",
    },
    ValidationDataConfig = new Aws.Bedrock.Inputs.CustomModelValidationDataConfigArgs
    {
        Validators = new[]
        {
            new Aws.Bedrock.Inputs.CustomModelValidationDataConfigValidatorArgs
            {
                S3Uri = "string",
            },
        },
    },
    VpcConfig = new Aws.Bedrock.Inputs.CustomModelVpcConfigArgs
    {
        SecurityGroupIds = new[]
        {
            "string",
        },
        SubnetIds = new[]
        {
            "string",
        },
    },
});
example, err := bedrock.NewCustomModel(ctx, "customModelResource", &bedrock.CustomModelArgs{
	JobName:             pulumi.String("string"),
	RoleArn:             pulumi.String("string"),
	CustomModelName:     pulumi.String("string"),
	BaseModelIdentifier: pulumi.String("string"),
	Hyperparameters: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	OutputDataConfig: &bedrock.CustomModelOutputDataConfigArgs{
		S3Uri: pulumi.String("string"),
	},
	CustomizationType:   pulumi.String("string"),
	CustomModelKmsKeyId: pulumi.String("string"),
	Tags: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Timeouts: &bedrock.CustomModelTimeoutsArgs{
		Create: pulumi.String("string"),
		Delete: pulumi.String("string"),
	},
	TrainingDataConfig: &bedrock.CustomModelTrainingDataConfigArgs{
		S3Uri: pulumi.String("string"),
	},
	ValidationDataConfig: &bedrock.CustomModelValidationDataConfigArgs{
		Validators: bedrock.CustomModelValidationDataConfigValidatorArray{
			&bedrock.CustomModelValidationDataConfigValidatorArgs{
				S3Uri: pulumi.String("string"),
			},
		},
	},
	VpcConfig: &bedrock.CustomModelVpcConfigArgs{
		SecurityGroupIds: pulumi.StringArray{
			pulumi.String("string"),
		},
		SubnetIds: pulumi.StringArray{
			pulumi.String("string"),
		},
	},
})
var customModelResource = new CustomModel("customModelResource", CustomModelArgs.builder()
    .jobName("string")
    .roleArn("string")
    .customModelName("string")
    .baseModelIdentifier("string")
    .hyperparameters(Map.of("string", "string"))
    .outputDataConfig(CustomModelOutputDataConfigArgs.builder()
        .s3Uri("string")
        .build())
    .customizationType("string")
    .customModelKmsKeyId("string")
    .tags(Map.of("string", "string"))
    .timeouts(CustomModelTimeoutsArgs.builder()
        .create("string")
        .delete("string")
        .build())
    .trainingDataConfig(CustomModelTrainingDataConfigArgs.builder()
        .s3Uri("string")
        .build())
    .validationDataConfig(CustomModelValidationDataConfigArgs.builder()
        .validators(CustomModelValidationDataConfigValidatorArgs.builder()
            .s3Uri("string")
            .build())
        .build())
    .vpcConfig(CustomModelVpcConfigArgs.builder()
        .securityGroupIds("string")
        .subnetIds("string")
        .build())
    .build());
custom_model_resource = aws.bedrock.CustomModel("customModelResource",
    job_name="string",
    role_arn="string",
    custom_model_name="string",
    base_model_identifier="string",
    hyperparameters={
        "string": "string",
    },
    output_data_config={
        "s3_uri": "string",
    },
    customization_type="string",
    custom_model_kms_key_id="string",
    tags={
        "string": "string",
    },
    timeouts={
        "create": "string",
        "delete": "string",
    },
    training_data_config={
        "s3_uri": "string",
    },
    validation_data_config={
        "validators": [{
            "s3_uri": "string",
        }],
    },
    vpc_config={
        "security_group_ids": ["string"],
        "subnet_ids": ["string"],
    })
const customModelResource = new aws.bedrock.CustomModel("customModelResource", {
    jobName: "string",
    roleArn: "string",
    customModelName: "string",
    baseModelIdentifier: "string",
    hyperparameters: {
        string: "string",
    },
    outputDataConfig: {
        s3Uri: "string",
    },
    customizationType: "string",
    customModelKmsKeyId: "string",
    tags: {
        string: "string",
    },
    timeouts: {
        create: "string",
        "delete": "string",
    },
    trainingDataConfig: {
        s3Uri: "string",
    },
    validationDataConfig: {
        validators: [{
            s3Uri: "string",
        }],
    },
    vpcConfig: {
        securityGroupIds: ["string"],
        subnetIds: ["string"],
    },
});
type: aws:bedrock:CustomModel
properties:
    baseModelIdentifier: string
    customModelKmsKeyId: string
    customModelName: string
    customizationType: string
    hyperparameters:
        string: string
    jobName: string
    outputDataConfig:
        s3Uri: string
    roleArn: string
    tags:
        string: string
    timeouts:
        create: string
        delete: string
    trainingDataConfig:
        s3Uri: string
    validationDataConfig:
        validators:
            - s3Uri: string
    vpcConfig:
        securityGroupIds:
            - string
        subnetIds:
            - string
CustomModel Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.
The CustomModel resource accepts the following input properties:
- BaseModel stringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- CustomModel stringName 
- Name for the custom model.
- Hyperparameters Dictionary<string, string>
- Parameters related to tuning the model.
- JobName string
- A name for the customization job.
- RoleArn string
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- CustomModel stringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- CustomizationType string
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- OutputData CustomConfig Model Output Data Config 
- S3 location for the output data.
- Dictionary<string, string>
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- Timeouts
CustomModel Timeouts 
- TrainingData CustomConfig Model Training Data Config 
- Information about the training dataset.
- ValidationData CustomConfig Model Validation Data Config 
- Information about the validation dataset.
- VpcConfig CustomModel Vpc Config 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- BaseModel stringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- CustomModel stringName 
- Name for the custom model.
- Hyperparameters map[string]string
- Parameters related to tuning the model.
- JobName string
- A name for the customization job.
- RoleArn string
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- CustomModel stringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- CustomizationType string
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- OutputData CustomConfig Model Output Data Config Args 
- S3 location for the output data.
- map[string]string
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- Timeouts
CustomModel Timeouts Args 
- TrainingData CustomConfig Model Training Data Config Args 
- Information about the training dataset.
- ValidationData CustomConfig Model Validation Data Config Args 
- Information about the validation dataset.
- VpcConfig CustomModel Vpc Config Args 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- baseModel StringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- customModel StringName 
- Name for the custom model.
- hyperparameters Map<String,String>
- Parameters related to tuning the model.
- jobName String
- A name for the customization job.
- roleArn String
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- customModel StringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- customizationType String
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- outputData CustomConfig Model Output Data Config 
- S3 location for the output data.
- Map<String,String>
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- timeouts
CustomModel Timeouts 
- trainingData CustomConfig Model Training Data Config 
- Information about the training dataset.
- validationData CustomConfig Model Validation Data Config 
- Information about the validation dataset.
- vpcConfig CustomModel Vpc Config 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- baseModel stringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- customModel stringName 
- Name for the custom model.
- hyperparameters {[key: string]: string}
- Parameters related to tuning the model.
- jobName string
- A name for the customization job.
- roleArn string
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- customModel stringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- customizationType string
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- outputData CustomConfig Model Output Data Config 
- S3 location for the output data.
- {[key: string]: string}
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- timeouts
CustomModel Timeouts 
- trainingData CustomConfig Model Training Data Config 
- Information about the training dataset.
- validationData CustomConfig Model Validation Data Config 
- Information about the validation dataset.
- vpcConfig CustomModel Vpc Config 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- base_model_ stridentifier 
- The Amazon Resource Name (ARN) of the base model.
- custom_model_ strname 
- Name for the custom model.
- hyperparameters Mapping[str, str]
- Parameters related to tuning the model.
- job_name str
- A name for the customization job.
- role_arn str
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- custom_model_ strkms_ key_ id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- customization_type str
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- output_data_ Customconfig Model Output Data Config Args 
- S3 location for the output data.
- Mapping[str, str]
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- timeouts
CustomModel Timeouts Args 
- training_data_ Customconfig Model Training Data Config Args 
- Information about the training dataset.
- validation_data_ Customconfig Model Validation Data Config Args 
- Information about the validation dataset.
- vpc_config CustomModel Vpc Config Args 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- baseModel StringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- customModel StringName 
- Name for the custom model.
- hyperparameters Map<String>
- Parameters related to tuning the model.
- jobName String
- A name for the customization job.
- roleArn String
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- customModel StringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- customizationType String
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- outputData Property MapConfig 
- S3 location for the output data.
- Map<String>
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- timeouts Property Map
- trainingData Property MapConfig 
- Information about the training dataset.
- validationData Property MapConfig 
- Information about the validation dataset.
- vpcConfig Property Map
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
Outputs
All input properties are implicitly available as output properties. Additionally, the CustomModel resource produces the following output properties:
- CustomModel stringArn 
- The ARN of the output model.
- Id string
- The provider-assigned unique ID for this managed resource.
- JobArn string
- The ARN of the customization job.
- JobStatus string
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- Dictionary<string, string>
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- TrainingMetrics List<CustomModel Training Metric> 
- Metrics associated with the customization job.
- ValidationMetrics List<CustomModel Validation Metric> 
- The loss metric for each validator that you provided.
- CustomModel stringArn 
- The ARN of the output model.
- Id string
- The provider-assigned unique ID for this managed resource.
- JobArn string
- The ARN of the customization job.
- JobStatus string
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- map[string]string
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- TrainingMetrics []CustomModel Training Metric 
- Metrics associated with the customization job.
- ValidationMetrics []CustomModel Validation Metric 
- The loss metric for each validator that you provided.
- customModel StringArn 
- The ARN of the output model.
- id String
- The provider-assigned unique ID for this managed resource.
- jobArn String
- The ARN of the customization job.
- jobStatus String
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- Map<String,String>
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- trainingMetrics List<CustomModel Training Metric> 
- Metrics associated with the customization job.
- validationMetrics List<CustomModel Validation Metric> 
- The loss metric for each validator that you provided.
- customModel stringArn 
- The ARN of the output model.
- id string
- The provider-assigned unique ID for this managed resource.
- jobArn string
- The ARN of the customization job.
- jobStatus string
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- {[key: string]: string}
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- trainingMetrics CustomModel Training Metric[] 
- Metrics associated with the customization job.
- validationMetrics CustomModel Validation Metric[] 
- The loss metric for each validator that you provided.
- custom_model_ strarn 
- The ARN of the output model.
- id str
- The provider-assigned unique ID for this managed resource.
- job_arn str
- The ARN of the customization job.
- job_status str
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- Mapping[str, str]
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- training_metrics Sequence[CustomModel Training Metric] 
- Metrics associated with the customization job.
- validation_metrics Sequence[CustomModel Validation Metric] 
- The loss metric for each validator that you provided.
- customModel StringArn 
- The ARN of the output model.
- id String
- The provider-assigned unique ID for this managed resource.
- jobArn String
- The ARN of the customization job.
- jobStatus String
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- Map<String>
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- trainingMetrics List<Property Map>
- Metrics associated with the customization job.
- validationMetrics List<Property Map>
- The loss metric for each validator that you provided.
Look up Existing CustomModel Resource
Get an existing CustomModel resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.
public static get(name: string, id: Input<ID>, state?: CustomModelState, opts?: CustomResourceOptions): CustomModel@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        base_model_identifier: Optional[str] = None,
        custom_model_arn: Optional[str] = None,
        custom_model_kms_key_id: Optional[str] = None,
        custom_model_name: Optional[str] = None,
        customization_type: Optional[str] = None,
        hyperparameters: Optional[Mapping[str, str]] = None,
        job_arn: Optional[str] = None,
        job_name: Optional[str] = None,
        job_status: Optional[str] = None,
        output_data_config: Optional[CustomModelOutputDataConfigArgs] = None,
        role_arn: Optional[str] = None,
        tags: Optional[Mapping[str, str]] = None,
        tags_all: Optional[Mapping[str, str]] = None,
        timeouts: Optional[CustomModelTimeoutsArgs] = None,
        training_data_config: Optional[CustomModelTrainingDataConfigArgs] = None,
        training_metrics: Optional[Sequence[CustomModelTrainingMetricArgs]] = None,
        validation_data_config: Optional[CustomModelValidationDataConfigArgs] = None,
        validation_metrics: Optional[Sequence[CustomModelValidationMetricArgs]] = None,
        vpc_config: Optional[CustomModelVpcConfigArgs] = None) -> CustomModelfunc GetCustomModel(ctx *Context, name string, id IDInput, state *CustomModelState, opts ...ResourceOption) (*CustomModel, error)public static CustomModel Get(string name, Input<string> id, CustomModelState? state, CustomResourceOptions? opts = null)public static CustomModel get(String name, Output<String> id, CustomModelState state, CustomResourceOptions options)resources:  _:    type: aws:bedrock:CustomModel    get:      id: ${id}- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- resource_name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- BaseModel stringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- CustomModel stringArn 
- The ARN of the output model.
- CustomModel stringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- CustomModel stringName 
- Name for the custom model.
- CustomizationType string
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- Hyperparameters Dictionary<string, string>
- Parameters related to tuning the model.
- JobArn string
- The ARN of the customization job.
- JobName string
- A name for the customization job.
- JobStatus string
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- OutputData CustomConfig Model Output Data Config 
- S3 location for the output data.
- RoleArn string
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- Dictionary<string, string>
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- Dictionary<string, string>
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- Timeouts
CustomModel Timeouts 
- TrainingData CustomConfig Model Training Data Config 
- Information about the training dataset.
- TrainingMetrics List<CustomModel Training Metric> 
- Metrics associated with the customization job.
- ValidationData CustomConfig Model Validation Data Config 
- Information about the validation dataset.
- ValidationMetrics List<CustomModel Validation Metric> 
- The loss metric for each validator that you provided.
- VpcConfig CustomModel Vpc Config 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- BaseModel stringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- CustomModel stringArn 
- The ARN of the output model.
- CustomModel stringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- CustomModel stringName 
- Name for the custom model.
- CustomizationType string
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- Hyperparameters map[string]string
- Parameters related to tuning the model.
- JobArn string
- The ARN of the customization job.
- JobName string
- A name for the customization job.
- JobStatus string
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- OutputData CustomConfig Model Output Data Config Args 
- S3 location for the output data.
- RoleArn string
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- map[string]string
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- map[string]string
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- Timeouts
CustomModel Timeouts Args 
- TrainingData CustomConfig Model Training Data Config Args 
- Information about the training dataset.
- TrainingMetrics []CustomModel Training Metric Args 
- Metrics associated with the customization job.
- ValidationData CustomConfig Model Validation Data Config Args 
- Information about the validation dataset.
- ValidationMetrics []CustomModel Validation Metric Args 
- The loss metric for each validator that you provided.
- VpcConfig CustomModel Vpc Config Args 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- baseModel StringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- customModel StringArn 
- The ARN of the output model.
- customModel StringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- customModel StringName 
- Name for the custom model.
- customizationType String
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- hyperparameters Map<String,String>
- Parameters related to tuning the model.
- jobArn String
- The ARN of the customization job.
- jobName String
- A name for the customization job.
- jobStatus String
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- outputData CustomConfig Model Output Data Config 
- S3 location for the output data.
- roleArn String
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- Map<String,String>
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- Map<String,String>
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- timeouts
CustomModel Timeouts 
- trainingData CustomConfig Model Training Data Config 
- Information about the training dataset.
- trainingMetrics List<CustomModel Training Metric> 
- Metrics associated with the customization job.
- validationData CustomConfig Model Validation Data Config 
- Information about the validation dataset.
- validationMetrics List<CustomModel Validation Metric> 
- The loss metric for each validator that you provided.
- vpcConfig CustomModel Vpc Config 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- baseModel stringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- customModel stringArn 
- The ARN of the output model.
- customModel stringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- customModel stringName 
- Name for the custom model.
- customizationType string
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- hyperparameters {[key: string]: string}
- Parameters related to tuning the model.
- jobArn string
- The ARN of the customization job.
- jobName string
- A name for the customization job.
- jobStatus string
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- outputData CustomConfig Model Output Data Config 
- S3 location for the output data.
- roleArn string
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- {[key: string]: string}
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- {[key: string]: string}
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- timeouts
CustomModel Timeouts 
- trainingData CustomConfig Model Training Data Config 
- Information about the training dataset.
- trainingMetrics CustomModel Training Metric[] 
- Metrics associated with the customization job.
- validationData CustomConfig Model Validation Data Config 
- Information about the validation dataset.
- validationMetrics CustomModel Validation Metric[] 
- The loss metric for each validator that you provided.
- vpcConfig CustomModel Vpc Config 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- base_model_ stridentifier 
- The Amazon Resource Name (ARN) of the base model.
- custom_model_ strarn 
- The ARN of the output model.
- custom_model_ strkms_ key_ id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- custom_model_ strname 
- Name for the custom model.
- customization_type str
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- hyperparameters Mapping[str, str]
- Parameters related to tuning the model.
- job_arn str
- The ARN of the customization job.
- job_name str
- A name for the customization job.
- job_status str
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- output_data_ Customconfig Model Output Data Config Args 
- S3 location for the output data.
- role_arn str
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- Mapping[str, str]
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- Mapping[str, str]
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- timeouts
CustomModel Timeouts Args 
- training_data_ Customconfig Model Training Data Config Args 
- Information about the training dataset.
- training_metrics Sequence[CustomModel Training Metric Args] 
- Metrics associated with the customization job.
- validation_data_ Customconfig Model Validation Data Config Args 
- Information about the validation dataset.
- validation_metrics Sequence[CustomModel Validation Metric Args] 
- The loss metric for each validator that you provided.
- vpc_config CustomModel Vpc Config Args 
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
- baseModel StringIdentifier 
- The Amazon Resource Name (ARN) of the base model.
- customModel StringArn 
- The ARN of the output model.
- customModel StringKms Key Id 
- The custom model is encrypted at rest using this key. Specify the key ARN.
- customModel StringName 
- Name for the custom model.
- customizationType String
- The customization type. Valid values: FINE_TUNING,CONTINUED_PRE_TRAINING.
- hyperparameters Map<String>
- Parameters related to tuning the model.
- jobArn String
- The ARN of the customization job.
- jobName String
- A name for the customization job.
- jobStatus String
- The status of the customization job. A successful job transitions from InProgresstoCompletedwhen the output model is ready to use.
- outputData Property MapConfig 
- S3 location for the output data.
- roleArn String
- The Amazon Resource Name (ARN) of an IAM role that Bedrock can assume to perform tasks on your behalf.
- Map<String>
- A map of tags to assign to the customization job and custom model. If configured with a provider default_tagsconfiguration block present, tags with matching keys will overwrite those defined at the provider-level.
- Map<String>
- Map of tags assigned to the resource, including those inherited from the provider default_tagsconfiguration block.
- timeouts Property Map
- trainingData Property MapConfig 
- Information about the training dataset.
- trainingMetrics List<Property Map>
- Metrics associated with the customization job.
- validationData Property MapConfig 
- Information about the validation dataset.
- validationMetrics List<Property Map>
- The loss metric for each validator that you provided.
- vpcConfig Property Map
- Configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for this job.
Supporting Types
CustomModelOutputDataConfig, CustomModelOutputDataConfigArgs          
- S3Uri string
- The S3 URI where the output data is stored.
- S3Uri string
- The S3 URI where the output data is stored.
- s3Uri String
- The S3 URI where the output data is stored.
- s3Uri string
- The S3 URI where the output data is stored.
- s3_uri str
- The S3 URI where the output data is stored.
- s3Uri String
- The S3 URI where the output data is stored.
CustomModelTimeouts, CustomModelTimeoutsArgs      
- Create string
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
- Delete string
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
- Create string
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
- Delete string
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
- create String
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
- delete String
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
- create string
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
- delete string
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
- create str
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
- delete str
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
- create String
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
- delete String
- A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
CustomModelTrainingDataConfig, CustomModelTrainingDataConfigArgs          
- S3Uri string
- The S3 URI where the training data is stored.
- S3Uri string
- The S3 URI where the training data is stored.
- s3Uri String
- The S3 URI where the training data is stored.
- s3Uri string
- The S3 URI where the training data is stored.
- s3_uri str
- The S3 URI where the training data is stored.
- s3Uri String
- The S3 URI where the training data is stored.
CustomModelTrainingMetric, CustomModelTrainingMetricArgs        
- TrainingLoss double
- Loss metric associated with the customization job.
- TrainingLoss float64
- Loss metric associated with the customization job.
- trainingLoss Double
- Loss metric associated with the customization job.
- trainingLoss number
- Loss metric associated with the customization job.
- training_loss float
- Loss metric associated with the customization job.
- trainingLoss Number
- Loss metric associated with the customization job.
CustomModelValidationDataConfig, CustomModelValidationDataConfigArgs          
- Validators
List<CustomModel Validation Data Config Validator> 
- Information about the validators.
- Validators
[]CustomModel Validation Data Config Validator 
- Information about the validators.
- validators
List<CustomModel Validation Data Config Validator> 
- Information about the validators.
- validators
CustomModel Validation Data Config Validator[] 
- Information about the validators.
- validators
Sequence[CustomModel Validation Data Config Validator] 
- Information about the validators.
- validators List<Property Map>
- Information about the validators.
CustomModelValidationDataConfigValidator, CustomModelValidationDataConfigValidatorArgs            
- S3Uri string
- The S3 URI where the validation data is stored.
- S3Uri string
- The S3 URI where the validation data is stored.
- s3Uri String
- The S3 URI where the validation data is stored.
- s3Uri string
- The S3 URI where the validation data is stored.
- s3_uri str
- The S3 URI where the validation data is stored.
- s3Uri String
- The S3 URI where the validation data is stored.
CustomModelValidationMetric, CustomModelValidationMetricArgs        
- ValidationLoss double
- The validation loss associated with the validator.
- ValidationLoss float64
- The validation loss associated with the validator.
- validationLoss Double
- The validation loss associated with the validator.
- validationLoss number
- The validation loss associated with the validator.
- validation_loss float
- The validation loss associated with the validator.
- validationLoss Number
- The validation loss associated with the validator.
CustomModelVpcConfig, CustomModelVpcConfigArgs        
- SecurityGroup List<string>Ids 
- VPC configuration security group IDs.
- SubnetIds List<string>
- VPC configuration subnets.
- SecurityGroup []stringIds 
- VPC configuration security group IDs.
- SubnetIds []string
- VPC configuration subnets.
- securityGroup List<String>Ids 
- VPC configuration security group IDs.
- subnetIds List<String>
- VPC configuration subnets.
- securityGroup string[]Ids 
- VPC configuration security group IDs.
- subnetIds string[]
- VPC configuration subnets.
- security_group_ Sequence[str]ids 
- VPC configuration security group IDs.
- subnet_ids Sequence[str]
- VPC configuration subnets.
- securityGroup List<String>Ids 
- VPC configuration security group IDs.
- subnetIds List<String>
- VPC configuration subnets.
Import
Using pulumi import, import Bedrock custom model using the job_arn. For example:
$ pulumi import aws:bedrock/customModel:CustomModel example arn:aws:bedrock:us-west-2:123456789012:model-customization-job/amazon.titan-text-express-v1:0:8k/1y5n57gh5y2e
To learn more about importing existing cloud resources, see Importing resources.
Package Details
- Repository
- AWS Classic pulumi/pulumi-aws
- License
- Apache-2.0
- Notes
- This Pulumi package is based on the awsTerraform Provider.