Model sources and license agreements

Amazon SageMaker JumpStart provides access to hundreds of publicly available and proprietary foundation models from third-party sources and partners. You can explore the JumpStart foundation model selection directly in the SageMaker AI console, Studio, or Studio Classic.

Licenses and model sources

Amazon SageMaker JumpStart provides access to both publicly available and proprietary foundation models. Foundation models are onboarded and maintained from third-party open source and proprietary providers. As such, they are released under different licenses as designated by the model source. Be sure to review the license for any foundation model that you use. 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 the content. Some examples of common foundation model licenses include:

Similarly, for any proprietary foundation models, be sure to review and comply with any terms of use and usage guidelines from the model provider. If you have questions about license information for a specific proprietary model, reach out to model provider directly. You can find model provider contact information in the Support tab of each model page in AWS Marketplace.

End-user license agreements

Some JumpStart foundation models require explicit acceptance of an end-user license agreement (EULA) before use.

EULA acceptance in Amazon SageMaker Studio

You may be prompted to accept an end-user license agreement before fine-tuning, deploying, or evaluating a JumpStart foundation model in Studio. To get started with JumpStart foundation models in Studio, see Use foundation models in Studio.

Some JumpStart foundation models require acceptance of an end-user license agreement before deployment. If this applies to the foundation model that you choose to use, Studio prompts you with a window containing the EULA content. 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.

EULA acceptance in Amazon SageMaker Studio Classic

You may be prompted to accept an end-user license agreement before deploying a JumpStart foundation model or opening a JumpStart foundation model notebook in Studio Classic. To get started with JumpStart foundation models in Studio Classic, see Use foundation models in Amazon SageMaker Studio Classic.

Some JumpStart foundation models require acceptance of an end-user license agreement before deployment. If this applies to the foundation model that you choose to use, Studio Classic prompts you with a window titled Review the End User License Agreement (EULA) and Acceptable Use Policy (AUP) below after you choose either Deploy or Open notebook. 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.

EULA acceptance with the SageMaker Python SDK

The following sections show you how to explicitly declare EULA acceptance when deploying or fine-tuning a JumpStart model with the SageMaker Python SDK. For more information on getting started with JumpStart foundation models using the SageMaker Python SDK, see Use foundation models with the SageMaker Python SDK.

Before you begin, make sure that you do the following:

EULA acceptance when deploying a JumpStart model

For models that require the acceptance of an end-user license agreement, you must explicitly declare EULA acceptance when deploying your JumpStart model.

from sagemaker.serve import ModelBuilder
from sagemaker.core.jumpstart.configs import JumpStartConfig

# Declare EULA acceptance in your JumpStart configuration
jumpstart_config = JumpStartConfig(
    model_id="meta-textgeneration-llama-2-13b",
    accept_eula=True,
)
model_builder = ModelBuilder.from_jumpstart_config(jumpstart_config=jumpstart_config)
model = model_builder.build()
endpoint = model_builder.deploy()

The accept_eula value is False by default. To accept the end-user license agreement, explicitly set it to True. For more information, see ModelBuilder in the SageMaker Python SDK documentation on the Read the Docs website.

EULA acceptance when fine-tuning a JumpStart model

For fine-tuning models that require the acceptance of an end-user license agreement, you must explicitly declare acceptance. Set this on the JumpStartConfig that you use to create your ModelTrainer. Fine-tuning a pre-trained model changes the weights of the original model. Therefore, when you deploy the fine-tuned model later, you do not need to accept a EULA.

from sagemaker.train import ModelTrainer
from sagemaker.train.configs import InputData
from sagemaker.core.jumpstart.configs import JumpStartConfig

# Declare EULA acceptance in your JumpStart configuration
jumpstart_config = JumpStartConfig(
    model_id="meta-textgeneration-llama-2-13b",
    accept_eula=False,
)
model_trainer = ModelTrainer.from_jumpstart_config(jumpstart_config=jumpstart_config)
model_trainer.train(
    input_data_config=[
        InputData(channel_name="train", data_source=training_dataset_s3_path),
        InputData(channel_name="validation", data_source=validation_dataset_s3_path),
    ]
)

The accept_eula value is False by default. To accept the end-user license agreement, explicitly set it to True on the JumpStartConfig. For more information, see SageMaker Train in the SageMaker Python SDK documentation on the Read the Docs website.