dstack-presets
This skill creates and manages dstack presets, which package model inference optimization configurations, benchmark results, and hardware specifications. Use it when explicitly asked to create presets or manage existing ones via dstack preset commands.
Instal·la
npx skillscat add dstackai/dstack/dstack-presets Instal·la des del registre de SkillsCat.
This skill creates and manages dstack presets, which package model inference optimization configurations, benchmark results, and hardware specifications. Use it when explicitly asked to create presets or manage existing ones via dstack preset commands.
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.
Categories
Instal·la
npx skillscat add dstackai/dstack/dstack-presets Instal·la des del registre de SkillsCat.