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AWS推出Ray Serve深度学习容器支持TorchServe
Simplify and support your TorchServe workloads using Ray Serve Deep Learning Containers
精选理由
AWS新容器帮你搞定TorchServe遗留问题，预装好所有组件，直接部署视觉语言模型。
AWS发布Ray Serve深度学习容器，解决TorchServe不再维护的问题。该容器已预装框架、GPU驱动和服务层。文章介绍如何在Amazon EKS上使用Ray Serve DLC在单个GPU节点部署视觉语言模型。容器经过预测试，支持完整GPU推理栈。
原文 · AWS Machine Learning Blog
Simplify and support your TorchServe workloads using Ray Serve Deep Learning Containers
TorchServe is no longer maintained, leaving teams to own the entire GPU inference stack. The AWS Ray Serve Deep Learning Container is a supported, pre-tested container with the framework, GPU drivers, and serving layer already assembled. This post walks through deploying a vision-language model on Amazon EKS using the Ray Serve DLC on a single GPU node.
