AboveParadise / LLMCBenchLinks
☆24Updated 9 months ago
Alternatives and similar repositories for LLMCBench
Users that are interested in LLMCBench are comparing it to the libraries listed below
Sorting:
- This repo contains the code for studying the interplay between quantization and sparsity methods☆23Updated 7 months ago
- Code Repository of Evaluating Quantized Large Language Models☆131Updated last year
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆65Updated 5 months ago
- [NeurIPS 2024 Oral🔥] DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs.☆167Updated 11 months ago
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆49Updated last year
- [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization☆38Updated last year
- [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer☆31Updated last year
- Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs☆18Updated 9 months ago
- The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…☆48Updated 2 years ago
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆38Updated last year
- ☆22Updated 10 months ago
- [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models☆61Updated last year
- [ICLR 2025] Official implementation of paper "Dynamic Low-Rank Sparse Adaptation for Large Language Models".☆22Updated 6 months ago
- D^2-MoE: Delta Decompression for MoE-based LLMs Compression☆65Updated 6 months ago
- LLM Inference with Microscaling Format☆31Updated 10 months ago
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆78Updated 11 months ago
- Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"☆72Updated 2 months ago
- The code repository of "MBQ: Modality-Balanced Quantization for Large Vision-Language Models"☆56Updated 6 months ago
- AFPQ code implementation☆23Updated last year
- [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference☆45Updated last year
- Code implementation of GPTAQ (https://arxiv.org/abs/2504.02692)☆63Updated last month
- Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…☆66Updated last year
- Official implementation of the EMNLP23 paper: Outlier Suppression+: Accurate quantization of large language models by equivalent and opti…☆47Updated last year
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆45Updated last year
- Awesome LLM pruning papers all-in-one repository with integrating all useful resources and insights.☆120Updated last month
- ☆29Updated last year
- A collection of research papers on low-precision training methods☆37Updated 4 months ago
- ☆59Updated last year
- This repo contains the source code for: Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs☆39Updated last year
- ☆51Updated last year