SqueezeLLM: Dense-and-Sparse Quantization
Paper
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2306.07629
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Published
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3
quant
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Norm Tweaking: High-performance Low-bit Quantization of Large Language Models
Paper • 2309.02784 • Published • 1 -
Extreme Compression of Large Language Models via Additive Quantization
Paper • 2401.06118 • Published • 9 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 48 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 21 -
APTQ: Attention-aware Post-Training Mixed-Precision Quantization for Large Language Models
Paper • 2402.14866 • Published -
EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs
Paper • 2403.02775 • Published • 11 -
GPTVQ: The Blessing of Dimensionality for LLM Quantization
Paper • 2402.15319 • Published • 19 -
COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization
Paper • 2403.07134 • Published -
OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models
Paper • 2306.02272 • Published -
QuantEase: Optimization-based Quantization for Language Models
Paper • 2309.01885 • Published • 4 -
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Paper • 2401.15024 • Published • 62 -
decoupleQ: Towards 2-bit Post-Training Uniform Quantization via decoupling Parameters into Integer and Floating Points
Paper • 2404.12759 • Published