Manage GPU compute resources and sandboxes via the Prime Intellect CLI.
npx skills add https://github.com/benediktstroebl/skills --skill prime-cli
Please help me install this Agent Skill. Skill: prime-cli Source: https://github.com/benediktstroebl/skills/tree/main/skills/prime-cli Command: npx skills add https://github.com/benediktstroebl/skills --skill prime-cli
Prime CLI provides a single interface to manage GPU compute, pods, sandboxes, machine learning environments, and deployment workflows on the Prime Intellect platform, reducing context switching and setup time for developers.
Login to Prime and list available GPU types to begin.
High-intent search queries and answers about installing and using this skill.
You can manage GPU compute resources and sandboxes by using a CLI to provision Docker-based environments, create pods, and orchestrate deployments for RL training and evaluations. It provides a single interface to reduce context switching.
Yes, you can provision Docker-based environments specifically for RL training, evaluations, and model deployments. The CLI orchestrates compute resources and manages sandboxes to support these machine learning workflows.
The best way to list available GPUs and create pods is through a comprehensive CLI that supports authentication, configuration, and environment setup. It also manages accounts, secrets, and teams for collaborative projects.
Yes, Prime CLI supports authentication and configuration management to streamline secure usage. You can login, configure environment settings, and manage access to GPU compute resources and sandboxes.
To start managing GPU pods and sandboxes, login to the platform and configure your environment settings via the CLI. This establishes secure access to provision compute resources and Docker-based environments for your deployments.
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