dstack
免费dstack is an open-source control plane for GPU provisioning and orchestration across GPU clouds, Kubernetes, and on-prem clusters.
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dstackai/dstack22842026年10月17日 更新
免费在 GitHub 公开
dstack-presets
Create and manage dstack presets: a toolkit that streamlines model inference optimization with agents, and a portable preset format. Use together with the dstack skill, and only when the user explicitly asks to create a preset or manage existing presets, not for deploying or serving a model.
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查看安装方法包含的文件（1）
- SKILL.md1.6 KB
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
dstack Presets
Use /dstack for CLI commands, YAML fields, apply behavior, fleets, and other
dstack syntax. This skill covers creating and managing presets.
Overview
Presets offer two things: a toolkit that streamlines model inference optimization using agents, and a portable format that deploys the final preset to any cloud, Kubernetes cluster, or bare-metal fleet. A preset holds the serving configuration that produced the result, the benchmark it reached, and the exact hardware it was verified on.
Presets are used for three kinds of work: finding an optimized baseline, optimizing through patching source code, and supporting new hardware.
When to use this skill:
- The user explicitly asks to create a preset, or to optimize model inference via a preset
- Managing already created presets: watching sessions, listing, exporting, and deleting them via
dstack presetcommands
When NOT to use this skill:
- Deploying or serving a model: use a service instead (see the
dstackskill)
How to use presets
Follow the presets documentation.
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同一仓库的技能
Use with the dstack skill for model-serving work when the image, serving command, resources, backend/fleet choice, or service behavior is not proven. Guides task-first prototyping on real hardware, choosing fleets/backends that can reuse idle instances and caches, checking vLLM/SGLang sources, and verifying the final dstack service with a model request.
中文简介正在准备中。当前显示原文说明。
dstackai/dstack22842026年10月17日 更新