Amazon SageMaker Unified Studio is in preview release and is subject to change.
Train models
Using Amazon SageMaker Unified Studio, you can train foundation models or custom models.
Follow these steps to train a foundation model:
-
Sign in to Amazon SageMaker Unified Studio using the link that your administrator gave you.
Choose a model to train.
-
From the main menu, choose Build.
-
From the drop-down menu, choose Jumpstart Models.
The JumpStart page lists the model providers.
-
Choose a model provider. The page displays the models for that provider.
-
Under Action, choose Trainable. The page displays the trainable models for that provider.
-
From the provider's list of models, choose the model you want to train.
-
-
From the model details page, choose Train to create a training job.
If the model is pretrained, you can fine-tune the model by adjusting the model parameters.
-
In the Fine-tuning model page, update the hyperparameters you want to change.
-
Enter Submit to submit the training job. You can view the training job from the Training jobs page.
You can also train the model in a Jupyterlab notebook using the SageMaker AI python SDK.
For more information about training models in JumpStart, see JumpStart pretrained models in the Amazon SageMaker AI Developer Guide.
