quark-torch-ptq
SkillAI & modelsTorch 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.
No other account needed.
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