quark-env-preflight

Collect OS, Python, GPU, and accelerator facts for Quark installation readiness.

154|27|Updated Jun 19, 2024
One-click install
npx skills add https://github.com/amd/Quark --skill quark-env-preflight
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: quark-env-preflight
Source: https://github.com/amd/Quark/tree/main/.claude/skills-impl/l0-foundation/shared/quark-env-preflight
Command: npx skills add https://github.com/amd/Quark --skill quark-env-preflight

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill collects and normalizes your machine’s environment facts so Quark installation and quantization decisions are based on confirmed OS, Python, GPU, and accelerator details instead of guesswork.

Core Features & Use Cases

  • Environment Discovery: Detects OS, Python version, container state, and virtual environment context.
  • Accelerator Identification: Distinguishes AMD ROCm, NVIDIA CUDA, CPU-only, or unknown setups and captures version signals when available.
  • Quark Readiness Checks: Helps determine whether your system is suitable for Quark install paths and downstream PTQ planning.
  • Use Case: Before installing Quark on a new workstation, use this Skill to verify whether the machine is running supported Python and the correct GPU backend.

Quick Start

Use the quark-env-preflight skill to inspect my current machine and summarize the OS, Python, GPU, and accelerator environment for Quark readiness.

Frequently Asked Questions about quark-env-preflight

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check my environment for Quark installation readiness?

To check Quark installation readiness, you must collect raw environment facts including OS, Python version, and GPU hardware. This preflight process normalizes machine details to validate accelerator compatibility for AMD ROCm, NVIDIA CUDA, or CPU-only systems before installing Quark.

Does Quark work with AMD ROCm and NVIDIA CUDA GPUs?

Quark supports AMD ROCm, NVIDIA CUDA, and CPU-only setups. Environment discovery distinguishes your specific accelerator backend and captures version signals to confirm your system is suitable for Quark install paths and downstream quantization planning.

What do I need to verify before installing Quark for quantization?

Before installing Quark, verify your OS, Python version, virtual environment context, and GPU backend. Detecting these environment facts ensures your workstation meets the confirmed hardware and software requirements for successful quantization planning.

How do I detect my GPU hardware and backend version for PyTorch?

Detect GPU hardware and backend versions for PyTorch by inspecting your machine for existing Quark or PyTorch installation details. This hardware discovery captures accelerator version signals for AMD ROCm or NVIDIA CUDA to confirm backend compatibility.

What are the limitations of running Quark in a containerized environment?

Running Quark in a containerized environment requires detecting your container state and virtual environment context. If preflight checks fail to identify supported Python versions or valid GPU backend signals, your system may be flagged as unknown or unsuitable for installation.