Run inference on Amazon SageMaker | Step 5: Serving hundreds of fine-tuned models

Опубликовано 24 июля 2024, 15:48

As the demands for personalized and specialized AI solutions grow, organizations are managing hundreds of fine-tuned models tailored to specific customer needs or use cases. The scalability and cost-effectiveness concerns of deploying and maintaining such a diverse model ecosystem have become challenging. In this video, you will learn how to use the performance optimizations of LoRA techniques in Amazon SageMaker large model inference (LMI) containers and inference components to help you efficiently manage and serve the growing portfolio of fine-tuned models while optimizing costs and providing seamless performance.

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