liyunqianggyn / Awesome-LLMs-PruningLinks
Awesome LLM pruning papers all-in-one repository with integrating all useful resources and insights.
☆88Updated 5 months ago
Alternatives and similar repositories for Awesome-LLMs-Pruning
Users that are interested in Awesome-LLMs-Pruning are comparing it to the libraries listed below
Sorting:
- Awesome list for LLM pruning.☆230Updated 5 months ago
- [NeurIPS 2024 Oral🔥] DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs.☆161Updated 8 months ago
- [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models☆51Updated last year
- ☆43Updated 7 months ago
- Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"☆66Updated 11 months ago
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆61Updated 2 months ago
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆68Updated 7 months ago
- Code Repository of Evaluating Quantized Large Language Models☆123Updated 8 months ago
- ☆54Updated 5 months ago
- QAQ: Quality Adaptive Quantization for LLM KV Cache☆50Updated last year
- ☆23Updated 3 weeks ago
- [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…☆65Updated last year
- Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…☆62Updated last year
- Official Implementation of SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks☆37Updated 4 months ago
- [ICML 2024] KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache☆303Updated 4 months ago
- Code associated with the paper **Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding**☆186Updated 3 months ago
- Spec-Bench: A Comprehensive Benchmark and Unified Evaluation Platform for Speculative Decoding (ACL 2024 Findings)☆272Updated last month
- Awesome list for LLM quantization☆223Updated 5 months ago
- ☆56Updated last year
- An algorithm for weight-activation quantization (W4A4, W4A8) of LLMs, supporting both static and dynamic quantization☆136Updated 2 weeks ago
- Unofficial implementations of block/layer-wise pruning methods for LLMs.☆69Updated last year
- Official PyTorch implementation of "IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact"☆44Updated 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
- SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs☆102Updated this week
- [ACL 2024] Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models☆89Updated last year
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆39Updated 11 months ago
- ☆42Updated 6 months ago
- ☆43Updated 11 months ago
- ☆20Updated last year
- Official implementation for Yuan & Liu & Zhong et al., KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark o…☆78Updated 3 months ago