Foundation model customization

Foundation models are extremely powerful models able to solve a wide array of tasks. To solve most tasks effectively, these models require some form of customization.

The recommended way to first customize a foundation model to a specific use case is through prompt engineering. Providing your foundation model with well-engineered, context-rich prompts can help achieve desired results without any fine-tuning or changing of model weights. For more information, see Prompt engineering for foundation models.

If prompt engineering alone is not enough to customize your foundation model to a specific task, you can fine-tune a foundation model on additional domain-specific data. For more information, see Foundation models and hyperparameters for fine-tuning. The fine-tuning process involves changing model weights.

If you want to customize your model with information from a knowledge library without any retraining, see Retrieval Augmented Generation.