DUCKQUANT / THE QUANT & AI DIRECTORY
1,058 resources, ranked by in-directory PageRank
Publication: FP8-BERT: Post-Training Quantization for Transformer. Published Dec 10, 2023.
Publication: CBQ: Cross-Block Quantization for Large Language Models. Published Dec 13, 2023.
Publication: ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative Tasks. Published Dec 14, 2023.
Publication: Extreme Compression of Large Language Models via Additive Quantization. Published Jan 11, 2024.
Publication: KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization. Published Jan 31, 2024.
Publication: OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models. Published Jun 4, 2023.
Publication: QIGen: Generating Efficient Kernels for Quantized Inference on Large Language Models. Published Jul 7, 2023.
Abstract page for arXiv paper 2306.08162: INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation
Publication: Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study. Published Jul 16, 2023.
Publication: Self-Distilled Quantization: Achieving High Compression Rates in Transformer-Based Language Models. Published Jul 12, 2023.
Publication: ZeroQuant-FP: A Leap Forward in LLMs Post-Training W4A8 Quantization Using Floating-Point Formats. Published Jul 19, 2023.
Publication: NUPES : Non-Uniform Post-Training Quantization via Power Exponent Search. Published Aug 10, 2023.
Publication: Gradient-Based Post-Training Quantization: Challenging the Status Quo. Published Aug 15, 2023.
Publication: FineQuant: Unlocking Efficiency with Fine-Grained Weight-Only Quantization for LLMs. Published Aug 16, 2023.
Publication: FPTQ: Fine-grained Post-Training Quantization for Large Language Models. Published Aug 30, 2023.
Publication: QuantEase: Optimization-based Quantization for Language Models. Published Sep 5, 2023.
Publication: Understanding the Impact of Post-Training Quantization on Large Language Models. Published Sep 11, 2023.
Publication: Norm Tweaking: High-performance Low-bit Quantization of Large Language Models. Published Sep 6, 2023.
Publication: Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs. Published Sep 11, 2023.
Publication: Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantization. Published Sep 24, 2023.
Publication: Efficient Post-training Quantization with FP8 Formats. Published Sep 26, 2023.
Publication: TEQ: Trainable Equivalent Transformation for Quantization of LLMs. Published Oct 17, 2023.
Publication: LLM-FP4: 4-Bit Floating-Point Quantized Transformers. Published Oct 25, 2023.
I-BERT: Integer-only BERT QuantizationSehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt KeutzerTransformer based models, lik...
Publication: Compression of Generative Pre-trained Language Models via Quantization. Published May 2022.
Publication: LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale. Published Aug 15, 2022.
Explore this resource at its source website for documentation and current information.
Publication: GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers. Published Oct 31, 2022.
Publication: SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models. Published Nov 18, 2022.
Publication: RPTQ: Reorder-based Post-training Quantization for Large Language Models. Published Apr 3, 2023.
Publication: Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling. Published Apr 18, 2023.
Publication: LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. Published May 29, 2023.
Publication: AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration. Published Jun 1, 2023.
Publication: PreQuant: A Task-agnostic Quantization Approach for Pre-trained Language Models. Published May 30, 2023.
