Enhancing GenAI performance with model tuning in Vertex AI
Foundation pre-trained models, despite their great out-of-the-box performance across a variety of generic tasks, sometimes fall short for specialized tasks, and prompt tuning alone cannot adequately address the performance gap. To bridge this gap, model tuning on Vertex AI can significantly enhance a model’s task-specific performance and ensure adherence to specific output requirements when standard instructions are inadequate. This section will provide insight into model tuning on Vertex AI.
Several compelling reasons exist for tuning LLMs:
- Improved performance: Tuning can significantly improve the accuracy, fluency, and relevance of LLM outputs for a particular task
- Domain adaptation: Tuning enables the specialization of LLMs for specific domains or types of data, ensuring that generated outputs are consistent with the domain’s terminology and style
- Bias mitigation: Tuning can help alleviate...
