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English(EN) 🤖 Simplify and support your TorchServe workloads using Ray Serve Deep Learning Containers TorchServe is no longer maintained, leaving teams to own the entire GP

AWS 通过新的 Ray Serve 深度学习容器简化 AI 推理

作者 PulseAugur 编辑部 · [2 个来源] ·

AWS 发布了新的深度学习容器 (DLCs)，利用 Ray Serve 来简化和支持以前由 TorchServe 管理的工作负载。TorchServe 不再积极维护，用户需要负责管理其整个依赖链，包括安全补丁和兼容性更新。AWS 提供的新的 Ray Serve DLCs 将框架、依赖项和 GPU 堆栈打包到经过测试、打补丁的 Docker 镜像中用于推理，旨在减少工程师的重复性工作并加快模型交付速度。 AI

影响 通过提供预构建、经过测试的推理环境，简化了 AI 模型的部署和维护。

排序理由 AWS 提供新的容器镜像，集成了现有技术来解决用户的问题。

在 Mastodon — mastodon.social 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

AWS 通过新的 Ray Serve 深度学习容器简化 AI 推理

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AWS 提供新的容器镜像，集成了现有技术来解决用户的问题。
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报道来源 [2]

  1. AWS Machine Learning Blog TIER_1 English(EN) · Ananth Raghavendra ·

    使用 Ray Serve 深度学习容器简化和支持您的 TorchServe 工作负载

    TorchServe is no longer maintained, leaving teams to own the entire GPU inference stack.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…

  2. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    🤖 使用 Ray Serve 深度学习容器简化和支持您的 TorchServe 工作负载 TorchServe 不再维护，团队需自行承担 GP 的全部责任

    🤖 Simplify and support your TorchServe workloads using Ray Serve Deep Learning Containers TorchServe is no longer maintained, leaving teams to own the entire GPU inference stack.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, GP…

    链接 aws.amazon.com/…/simplify-and-support-you…

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