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 awq?
firecrawl/ai-research-skills/awq
$npx -y skills add firecrawl/ai-research-skills --skill awqInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/firecrawl/ai-research-skills" --skill "firecrawl/ai-research-skills/awq"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/firecrawl/ai-research-skills" that are relevant to the current task. Run `npx skills add "https://github.com/firecrawl/ai-research-skills"` and select the relevant skills, then follow their instructions.
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