awq-quantization

SKILLWorkflowcommunity
v0.0.0Orchestra-ResearchMITUpdated 2mo agoSource →

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

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2mo agoLast update
Skill
AuthorOrchestra-Research
Version0.0.0
LicenseMIT
CategoryWorkflow
Formatsskill.md
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Claude✓ Supported
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Gemini
About

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.

Keywords
skillclaude