yxli2123 / LoSparseLinks
☆57Updated last year
Alternatives and similar repositories for LoSparse
Users that are interested in LoSparse are comparing it to the libraries listed below
Sorting:
- [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models☆54Updated last year
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆47Updated last year
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆61Updated 2 months ago
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆71Updated 8 months ago
- SQUEEZED ATTENTION: Accelerating Long Prompt LLM Inference☆47Updated 7 months ago
- This repo contains the source code for: Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs☆38Updated 10 months ago
- [ICML 2024] SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models☆21Updated last year
- [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…☆65Updated last year
- Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"☆69Updated 11 months ago
- ☆50Updated last year
- [ICLR 2024 Spotlight] Code for the paper "Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy"☆85Updated this week
- ☆37Updated 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
- ☆18Updated 6 months ago
- Official implementation for LaCo (EMNLP 2024 Findings)☆17Updated 8 months ago
- [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference☆39Updated last year
- Official Implementation of SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks☆37Updated 4 months ago
- ☆10Updated last year
- Official code for the paper "Examining Post-Training Quantization for Mixture-of-Experts: A Benchmark"☆20Updated last year
- Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding (EMNLP 2023 Long)☆60Updated 8 months ago
- ☆28Updated 11 months ago
- [ICML24] Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for LLMs☆84Updated 7 months ago
- QAQ: Quality Adaptive Quantization for LLM KV Cache☆51Updated last year
- ☆55Updated 6 months ago
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆39Updated last year
- ☆46Updated last year
- Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs☆19Updated 6 months ago
- [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…☆52Updated 2 years ago
- The official implementation of the paper "Towards Efficient Mixture of Experts: A Holistic Study of Compression Techniques (TMLR)".☆71Updated 3 months ago
- [ACL 2024] Official PyTorch implementation of "IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact"☆44Updated last year