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awq-quantization

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

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Install

armory install awq-quantization --cli claude

writes the skill into.claude/skills/awq-quantization/SKILL.mdListed as compatible

Configuration
# fetches the source and writes it to:
.claude/skills/awq-quantization/SKILL.md

Needs the armory CLI · not on npm yet, build it from cli/ in the repository

What it is

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

When to use it

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

How to install / invoke

# Copy the skill into your .claude/skills/ directory
curl -sL https://raw.githubusercontent.com/davila7/claude-code-templates/main/cli-tool/components/skills/ai-research/optimization-awq/SKILL.md -o .claude/skills/optimization-awq/SKILL.md

Notes

Extracted from davila7/claude-code-templates, optimization-awq category.