quark-torch-ptq

SkillAI & models

Torch LLM PTQ workflow for AMD Quark — for PyTorch / HuggingFace transformers models (safetensors input). Use when the user wants a complete PTQ pipeline: model inspection, quantization planning, script generation, and optional execution. Stops at the quantized output. Trigger for "quantize my model", "run PTQ", "run model quantization", "full quantization pipeline", "quantize Llama/Qwen/Mistral with FP8/INT4", or any request that spans more than one PTQ step. For a run that also validates and evaluates accuracy use quark-torch-llm-ptq-eval. Not for .onnx input models — use quark-onnx-ptq instead.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the quark-torch-ptq skill

What this skill tells your AI

The instructions your AI receives, as published by amd/quark in .claude/skills/quark-torch-ptq/SKILL.md and read by ahel’s review.

Read and follow the instructions in .claude/skills-impl/l2-workflows/torch/quark-torch-llm-ptq-workflow/SKILL.md.

Signals

GitHub stars
166
Forks
33
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
quark-torch-ptq
Source
github.com/amd/quark