Tuning Studio
Tune a foundation model with the Tuning Studio to customize the model for your needs.
- Required permissions
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To run tuning experiments, you must have the Admin or Editor role in a project.
- Required credentials
- Data format
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Tabular: JSON, JSONL
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Note: You can use the same training data with one or more tuning experiments.
- Data size
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50 to 10,000 input and output example pairs. The maximum file size is 200 MB.
The Tuning Studio is not available with all plans or in all data centers. The foundation models that are available for tuning in the Tuning Studio can also differ by data center. For more information, see watsonx.ai Runtime plans and Regional availability for services and features.
Before you begin
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Make decisions about the following tuning options:
- Choose the tuning method to use. See Tuning methods.
- Find the foundation model that works best for your use case. See Choosing a foundation model to tune.
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Create a set of example prompts to use as training data for tuning the foundation model. See Data formats.
Procedure
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From within a project, go to the Assets tab, click New Asset, and then click New asset > Tune a foundation model with labeled data.
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Name the tuning experiment.
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Optional: Add a description and tags. Add a description as a reminder to yourself and to help collaborators understand the goal of the tuned model. Assigning a tag gives you a way to filter your tuning assets later to show only the assets associated with a tag.
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Click Create.
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Click Select a foundation model to choose the foundation model that you want to tune.
Click a tile to see a model card with details about the foundation model. When you find the foundation model that you want to use, click Select.
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Customize the tuning experiment parameters. For details, see Fine tuning.
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Evaluate the results of your tuning experiment after the experiment. If necessary, change the training data or the experiment parameters and run more experiments until you're satisfied with the results. See Evaluating the tuning experiment.
What to do next
A tuned model asset is not created until after you create a deployment from a completed tuning experiment. For more information, see Deploying tuned models.