Deploy decision models with llama.cpp on Amazon SageMaker AI
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Learn how to deploy decision models with llama.cpp on Amazon SageMaker AI. This technical how-to serves OpenAI-compatible chat completions with the AWS Deep Learning Container for llama.cpp, then extends the runtime with SemIf to return probabilities over declared options on CPU or GPU.
Applications that route requests, select agent actions, or assign policy outcomes often need scores over a fixed set of choices instead of free-form text. Deploying these decision models with llama.cpp on Amazon SageMaker AI gives you a managed path for serving quantized models on CPU or GPU infrastructure. This post continues a series on specialized AWS Deep Learning Containers (DLCs) for generative AI inference. Previous posts cover WhisperX , vLLM-Omni – Part 1 , and vLLM-Omni – Part 2 . In…
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