Summary
This blog post addresses how to efficiently perform large-scale batch inference using the CodeFlare SDK with Ray Data and vLLM on OpenShift AI. It highlights the distinction between online and offline inference, and offers a step-by-step guide for setting up a remote batch inference job, detailing configuration, model sourcing, performance tuning, and job submission to a Ray cluster. It emphasizes that data scientists can leverage these tools without deep infrastructure knowledge.