Remove Auto-complete Remove Explainability Remove Inference Engine
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SGLang: Efficient Execution of Structured Language Model Programs

Unite.AI

These new use cases necessitate multiple, often dependent, LLM generation calls, indicating a trend of using multi-call structures to complete complex tasks. State-of-the-art inference engines, optimized to reduce latency and improve throughput, lack direct knowledge of the workload, resulting in significant inefficiencies.

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Build a personalized avatar with generative AI using Amazon SageMaker

AWS Machine Learning Blog

base model using SageMaker asynchronous inference. We explain the rationale for using an inference endpoint for training later in this post. We explain each step in more detail in the following sections and walk through some of the sample code snippets. To host the asynchronous endpoint, we must complete several steps.