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Collections including paper arxiv:2309.02784

XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference

Paper • 2404.15420 • Published Apr 23, 2024 • 11
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework

Paper • 2404.14619 • Published Apr 22, 2024 • 126
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22, 2024 • 259
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 45

SqueezeLLM: Dense-and-Sparse Quantization

Paper • 2306.07629 • Published Jun 13, 2023 • 4
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models

Paper • 2309.02784 • Published Sep 6, 2023 • 2
Extreme Compression of Large Language Models via Additive Quantization

Paper • 2401.06118 • Published Jan 11, 2024 • 14
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 50

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 27
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models

Paper • 2309.02784 • Published Sep 6, 2023 • 2
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1

Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing

Paper • 2306.12929 • Published Jun 22, 2023 • 12
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models

Paper • 2309.02784 • Published Sep 6, 2023 • 2
QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models

Paper • 2310.08041 • Published Oct 12, 2023 • 1
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 627

QuIP: 2-Bit Quantization of Large Language Models With Guarantees

Paper • 2307.13304 • Published Jul 25, 2023 • 2
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Paper • 2306.03078 • Published Jun 5, 2023 • 3
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Paper • 2308.13137 • Published Aug 25, 2023 • 18
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Paper • 2306.00978 • Published Jun 1, 2023 • 11

XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference

Paper • 2404.15420 • Published Apr 23, 2024 • 11
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework

Paper • 2404.14619 • Published Apr 22, 2024 • 126
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22, 2024 • 259
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 45

Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing

Paper • 2306.12929 • Published Jun 22, 2023 • 12
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models

Paper • 2309.02784 • Published Sep 6, 2023 • 2
QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models

Paper • 2310.08041 • Published Oct 12, 2023 • 1
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 627

SqueezeLLM: Dense-and-Sparse Quantization

Paper • 2306.07629 • Published Jun 13, 2023 • 4
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models

Paper • 2309.02784 • Published Sep 6, 2023 • 2
Extreme Compression of Large Language Models via Additive Quantization

Paper • 2401.06118 • Published Jan 11, 2024 • 14
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 50

QuIP: 2-Bit Quantization of Large Language Models With Guarantees

Paper • 2307.13304 • Published Jul 25, 2023 • 2
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Paper • 2306.03078 • Published Jun 5, 2023 • 3
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Paper • 2308.13137 • Published Aug 25, 2023 • 18
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Paper • 2306.00978 • Published Jun 1, 2023 • 11

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 27
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models

Paper • 2309.02784 • Published Sep 6, 2023 • 2
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1

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