imagination-research / EEPLinks
Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs
☆21Updated last month
Alternatives and similar repositories for EEP
Users that are interested in EEP are comparing it to the libraries listed below
Sorting:
- [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization☆38Updated last year
- [ICLR 2025] Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better☆16Updated 9 months ago
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆47Updated last year
- [COLM 2025] Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"☆61Updated 5 months ago
- This repo contains the code for studying the interplay between quantization and sparsity methods☆24Updated 9 months ago
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆82Updated last year
- ☆26Updated last year
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆50Updated last year
- ☆30Updated last year
- ☆62Updated 2 years ago
- LLM Inference with Microscaling Format☆33Updated last year
- [ACL 2025] Squeezed Attention: Accelerating Long Prompt LLM Inference☆54Updated last year
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆67Updated 8 months ago
- ☆24Updated last year
- This repo contains the source code for: Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs☆42Updated last year
- The code repository of "MBQ: Modality-Balanced Quantization for Large Vision-Language Models"☆68Updated 8 months ago
- Code Repository of Evaluating Quantized Large Language Models☆137Updated last year
- [ICLR 2025] Official implementation of paper "Dynamic Low-Rank Sparse Adaptation for Large Language Models".☆23Updated 8 months ago
- ☆31Updated last year
- Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"☆74Updated 5 months ago
- [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer☆30Updated 2 years ago
- ☆49Updated last year
- [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…☆67Updated last year
- [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference☆46Updated last year
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆39Updated last year
- Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…☆68Updated last year
- [ICML 2024] SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models☆21Updated last year
- ☆60Updated last year
- [ICLR 2025] Mixture Compressor for Mixture-of-Experts LLMs Gains More☆63Updated 9 months ago
- [ICML 2025] SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models☆46Updated last year