LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale
Paper
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2208.07339
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Published
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5
Quantization Reading-List
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GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
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SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
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QLoRA: Efficient Finetuning of Quantized LLMs
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AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
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QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
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LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
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BitNet: Scaling 1-bit Transformers for Large Language Models
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FP8-LM: Training FP8 Large Language Models
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GPTVQ: The Blessing of Dimensionality for LLM Quantization
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
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MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design
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Matryoshka Quantization
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BitNet b1.58 2B4T Technical Report
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BitNet v2: Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs
Paper • 2504.18415 • Published • 49 -
TernaryLLM: Ternarized Large Language Model
Paper • 2406.07177 • Published • 1 -
SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot
Paper • 2301.00774 • Published • 4