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cupynumeric-install

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Safe cuPyNumeric install and verify.

Software Engineering#pip#verification#gpu#installation#cuda#conda#cupynumeric
Authorsayalinvidia
Version1.0.0
Installs0

System Documentation

What problem does it solve?

cuPyNumeric installation and verification is often error-prone due to environment fragmentation (Python versions, package managers, and GPU vs CPU variants). This Skill provides a safe, guided flow that helps you install cuPyNumeric in an isolated environment (conda or pip), verify prerequisites (CUDA, Python version), and confirm the runtime can run a basic check without modifying system Python or base environments.

Core Features & Use Cases

  • Isolated environment setup (conda or virtualenv) to prevent polluting the system Python.
  • Preflight prerequisites validation (CUDA version, supported Python, OS) and guidance for GPU vs CPU builds.
  • Step-by-step install and verification workflow with a smoke-test to ensure the installation works.

Quick Start

Follow the isolated-environment install and verification steps to install cuPyNumeric and confirm GPU or CPU operation.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: cupynumeric-install
Download link: https://github.com/sayalinvidia/sayali-skills-test/archive/main.zip#cupynumeric-install

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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