ServerlessJobConfig ¶

class ServerlessJobConfig(TypedDict, closed=True):
    base_model_arn: (
        "capo_sagemaker.types.serverless_job_base_model_arn.ServerlessJobBaseModelArn"
    )
    """<p> The base model Amazon Resource Name (ARN) in <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/jumpstart-foundation-models-use.html">SageMaker Public Hub</a>. SageMaker always selects the latest version of the provided model. </p>"""
    accept_eula: NotRequired["capo_sagemaker.types.accept_eula.AcceptEula"]
    """<p> Specifies agreement to the model end-user license agreement (EULA). The <code>AcceptEula</code> value must be explicitly defined as <code>True</code> in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/jumpstart-foundation-models-choose.html#jumpstart-foundation-models-choose-eula">End-user license agreements</a> section for more details on accepting the EULA. </p>"""
    job_type: "capo_sagemaker.types.serverless_job_type.ServerlessJobType"
    """<p> The serverless training job type. </p>"""
    customization_technique: NotRequired[
        "capo_sagemaker.types.customization_technique.CustomizationTechnique"
    ]
    """<p> The model customization technique. </p>"""
    peft: NotRequired["capo_sagemaker.types.peft.Peft"]
    """<p> The parameter-efficient fine-tuning configuration. </p>"""
    evaluation_type: NotRequired["capo_sagemaker.types.evaluation_type.EvaluationType"]
    """<p> The evaluation job type. Required when serverless job type is <code>Evaluation</code>. </p>"""
    evaluator_arn: NotRequired["capo_sagemaker.types.evaluator_arn.EvaluatorArn"]
    """<p> The evaluator Amazon Resource Name (ARN) used as reward function or reward prompt. </p>"""
    sequence_length: NotRequired["capo_sagemaker.types.sequence_length.SequenceLength"]
    """<p> The maximum sequence length, in tokens, that the customization job supports. SageMaker uses this value to select a training configuration for the base model that you specify. The parameter supports the following values: </p> <ul> <li> <p> <code>1K</code> </p> </li> <li> <p> <code>2K</code> </p> </li> <li> <p> <code>4K</code> </p> </li> <li> <p> <code>8K</code> </p> </li> <li> <p> <code>16K</code> </p> </li> <li> <p> <code>32K</code> </p> </li> <li> <p> <code>64K</code> </p> </li> <li> <p> <code>128K</code> </p> </li> </ul> <p> If you don't specify a value, SageMaker selects a training configuration based on the other values that you specify. The selection is not restricted to a particular sequence length. </p>"""