ptq
OfficialQuantize pretrained models with ModelOpt PTQ.
AuthorNVIDIA
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Post-training quantization (PTQ) enables converting pretrained models into compact, deployment-friendly checkpoints with reduced memory footprint and faster inference using ModelOpt.
Core Features & Use Cases
- Supports nvfp4, fp8, and int4_awq formats for HF, MoE, and VLM backbones.
- Automates calibration, validation, and export of quantized checkpoints.
- Use Case: quantize a Qwen3-0.6B to nvfp4 for deployment on GPU-constrained environments.
Quick Start
Quantize a pretrained model to produce a deployment-ready quantized checkpoint using ModelOpt PTQ.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 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: ptq Download link: https://github.com/NVIDIA/skills/archive/main.zip#ptq Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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