ZhengaoLi / DISP-LLM-Dimension-Independent-Structural-Pruning
An implementation of the DISP-LLM method from the NeurIPS 2024 paper: Dimension-Independent Structural Pruning for Large Language Models.
☆19Updated last month
Alternatives and similar repositories for DISP-LLM-Dimension-Independent-Structural-Pruning
Users that are interested in DISP-LLM-Dimension-Independent-Structural-Pruning are comparing it to the libraries listed below
Sorting:
- ☆41Updated 11 months ago
- ☆10Updated last year
- Github Repo for OATS: Outlier-Aware Pruning through Sparse and Low Rank Decomposition☆12Updated last month
- A curated list of early exiting (LLM, CV, NLP, etc)☆48Updated 8 months ago
- ☆51Updated last year
- Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs☆16Updated 5 months ago
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆47Updated last year
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆45Updated last year
- Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"☆66Updated 10 months ago
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆31Updated 2 years ago
- ☆23Updated this week
- [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models☆49Updated last year
- Awesome LLM pruning papers all-in-one repository with integrating all useful resources and insights.☆86Updated 5 months ago
- This repo contains the code for studying the interplay between quantization and sparsity methods☆19Updated 2 months ago
- Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…☆61Updated last year
- [ICML 2024] Official code for the paper "Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark ".☆102Updated 10 months ago
- ☆28Updated 9 months ago
- This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).☆46Updated 2 years ago
- ☆10Updated 6 months ago
- Efficient LLM Inference Acceleration using Prompting☆47Updated 6 months ago
- ☆18Updated last year
- Awesome list for LLM pruning.☆224Updated 5 months ago
- Official Implementation of Robustifying and Boosting Training-Free Neural Architecture Search☆11Updated last year
- Code for the NeurIPS 2022 paper "Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning".☆119Updated last year
- [ICML 2021] "Double-Win Quant: Aggressively Winning Robustness of Quantized DeepNeural Networks via Random Precision Training and Inferen…☆13Updated 3 years ago
- The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…☆47Updated 2 years ago
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆58Updated last month
- [ICDCS 2023] Evaluation and Optimization of Gradient Compression for Distributed Deep Learning☆10Updated 2 years ago
- ☆8Updated 7 months ago
- Official implementation for Yuan & Liu & Zhong et al., KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark o…☆78Updated 2 months ago