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CreateModelCustomizationJobRequest

Source code in docs_src/capo_bedrock/types/create_model_customization_job_request.py
class CreateModelCustomizationJobRequest(TypedDict, closed=True):
    job_name: "capo_bedrock.types.job_name.JobName"
    """<p>A name for the fine-tuning job.</p>"""
    custom_model_name: "capo_bedrock.types.custom_model_name.CustomModelName"
    """<p>A name for the resulting custom model.</p>"""
    role_arn: "capo_bedrock.types.role_arn.RoleArn"
    """<p>The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. For example, during model training, Amazon Bedrock needs your permission to read input data from an S3 bucket, write model artifacts to an S3 bucket. To pass this role to Amazon Bedrock, the caller of this API must have the <code>iam:PassRole</code> permission. </p>"""
    client_request_token: NotRequired[
        "capo_bedrock.types.idempotency_token.IdempotencyToken"
    ]
    """<p>A unique, case-sensitive identifier to ensure that the API request 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 <a href="https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Run_Instance_Idempotency.html">Ensuring idempotency</a>.</p>"""
    base_model_identifier: (
        "capo_bedrock.types.base_model_identifier.BaseModelIdentifier"
    )
    """<p>Name of the base model.</p>"""
    customization_type: NotRequired[
        "capo_bedrock.types.customization_type.CustomizationType"
    ]
    """<p>The customization type.</p>"""
    custom_model_kms_key_id: NotRequired["capo_bedrock.types.kms_key_id.KmsKeyId"]
    """<p>The custom model is encrypted at rest using this key.</p>"""
    job_tags: NotRequired["capo_bedrock.types.tag_list.TagList"]
    """<p>Tags to attach to the job.</p>"""
    custom_model_tags: NotRequired["capo_bedrock.types.tag_list.TagList"]
    """<p>Tags to attach to the resulting custom model.</p>"""
    training_data_config: "capo_bedrock.types.training_data_config.TrainingDataConfig"
    """<p>Information about the training dataset.</p>"""
    validation_data_config: NotRequired[
        "capo_bedrock.types.validation_data_config.ValidationDataConfig"
    ]
    """<p>Information about the validation dataset. </p>"""
    output_data_config: "capo_bedrock.types.output_data_config.OutputDataConfig"
    """<p>S3 location for the output data.</p>"""
    hyper_parameters: NotRequired[
        "capo_bedrock.types.model_customization_hyper_parameters.ModelCustomizationHyperParameters"
    ]
    """<p>Parameters related to tuning the model. For details on the format for different models, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models-hp.html">Custom model hyperparameters</a>.</p>"""
    vpc_config: NotRequired["capo_bedrock.types.vpc_config.VpcConfig"]
    """<p>The configuration of the Virtual Private Cloud (VPC) that contains the resources that you're using for this job. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/vpc-model-customization.html">Protect your model customization jobs using a VPC</a>.</p>"""
    customization_config: NotRequired[
        "capo_bedrock.types.customization_config.CustomizationConfig"
    ]
    """<p>The customization configuration for the model customization job.</p>"""

base_model_identifier instance-attribute

base_model_identifier: BaseModelIdentifier

Name of the base model.

client_request_token instance-attribute

client_request_token: NotRequired[IdempotencyToken]

A unique, case-sensitive identifier to ensure that the API request 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.

custom_model_kms_key_id instance-attribute

custom_model_kms_key_id: NotRequired[KmsKeyId]

The custom model is encrypted at rest using this key.

custom_model_name instance-attribute

custom_model_name: CustomModelName

A name for the resulting custom model.

custom_model_tags instance-attribute

custom_model_tags: NotRequired[TagList]

Tags to attach to the resulting custom model.

customization_config instance-attribute

customization_config: NotRequired[CustomizationConfig]

The customization configuration for the model customization job.

customization_type instance-attribute

customization_type: NotRequired[CustomizationType]

The customization type.

hyper_parameters instance-attribute

hyper_parameters: NotRequired[ModelCustomizationHyperParameters]

Parameters related to tuning the model. For details on the format for different models, see Custom model hyperparameters.

job_name instance-attribute

job_name: JobName

A name for the fine-tuning job.

job_tags instance-attribute

job_tags: NotRequired[TagList]

Tags to attach to the job.

output_data_config instance-attribute

output_data_config: OutputDataConfig

S3 location for the output data.

role_arn instance-attribute

role_arn: RoleArn

The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. For example, during model training, Amazon Bedrock needs your permission to read input data from an S3 bucket, write model artifacts to an S3 bucket. To pass this role to Amazon Bedrock, the caller of this API must have the iam:PassRole permission.

training_data_config instance-attribute

training_data_config: TrainingDataConfig

Information about the training dataset.

validation_data_config instance-attribute

validation_data_config: NotRequired[ValidationDataConfig]

Information about the validation dataset.

vpc_config instance-attribute

vpc_config: NotRequired[VpcConfig]

The configuration of the Virtual Private Cloud (VPC) that contains the resources that you're using for this job. For more information, see Protect your model customization jobs using a VPC.