UNITES-Lab / moe-quantizationLinks
Official code for the paper "Examining Post-Training Quantization for Mixture-of-Experts: A Benchmark"
☆28Updated 7 months ago
Alternatives and similar repositories for moe-quantization
Users that are interested in moe-quantization are comparing it to the libraries listed below
Sorting:
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆88Updated last year
- [ICML 2025] SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models☆51Updated last year
- This repo contains the source code for: Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs☆44Updated last year
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆48Updated last year
- ☆158Updated 11 months ago
- ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization☆112Updated last year
- ☆31Updated last year
- Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs☆23Updated 2 months ago
- [ICML 2024] Official Implementation of SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks☆39Updated last year
- ☆30Updated last year
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆67Updated 10 months ago
- The official implementation of the paper "Towards Efficient Mixture of Experts: A Holistic Study of Compression Techniques (TMLR)".☆88Updated 10 months ago
- [ACL 2025] Squeezed Attention: Accelerating Long Prompt LLM Inference☆56Updated last year
- An algorithm for weight-activation quantization (W4A4, W4A8) of LLMs, supporting both static and dynamic quantization☆172Updated 2 months ago
- An unofficial implementation of "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆36Updated last year
- Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"☆79Updated 7 months ago
- SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs☆188Updated 4 months ago
- ☆131Updated 8 months ago
- LLM Inference with Microscaling Format☆34Updated last year
- [COLM 2025] Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"☆67Updated 6 months ago
- ☆25Updated last year
- [CoLM'25] The official implementation of the paper <MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression>☆155Updated 3 weeks ago
- GEAR: An Efficient KV Cache Compression Recipefor Near-Lossless Generative Inference of LLM☆176Updated last year
- 16-fold memory access reduction with nearly no loss☆110Updated 10 months ago
- [ICML 2024 Oral] Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs☆123Updated 7 months ago
- [ICLR 2025] Palu: Compressing KV-Cache with Low-Rank Projection☆154Updated 11 months ago
- HALO: Hadamard-Assisted Low-Precision Optimization and Training method for finetuning LLMs. 🚀 The official implementation of https://arx…☆29Updated 11 months ago
- Official implementation for Training LLMs with MXFP4☆118Updated 9 months ago
- ☆60Updated last year
- Unofficial implementations of block/layer-wise pruning methods for LLMs.☆77Updated last year