Stage any supported open-weight Hugging Face model directly into Amazon S3 and deploy it to an Amazon SageMaker AI real-time endpoint with a compatible vLLM or SGLang Deep Learning Container. Use for model hosting, endpoint creation, direct-to-S3 transfer,…
aws-samples/sample-sagemaker-agentic-model-deployment
SkillsMP has collected 3 skills from aws-samples/sample-sagemaker-agentic-model-deployment. Open a skill to review its source and details.
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occupation
Software Developers
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Software Developers
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Run a managed performance benchmark against a deployed Amazon SageMaker AI endpoint using SageMaker AI inference benchmarking (part of optimized GenAI inference recommendations; NVIDIA AIPerf under the hood). Measures TTFT, ITL, request-latency percentiles,…
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occupation
Software Developers
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Find an optimized serving configuration for a model with Amazon SageMaker AI inference recommendations, then deploy it and compare against a baseline benchmark. Covers both config search (best instance + serving knobs) and deep optimization (speculative…
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Showing 3 of 3 collected skills.