JarvisPei / CMoELinks
Implementation for the paper: CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference
☆21Updated 3 months ago
Alternatives and similar repositories for CMoE
Users that are interested in CMoE are comparing it to the libraries listed below
Sorting:
- [ICML24] Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for LLMs☆84Updated 7 months ago
- LLM Inference with Microscaling Format☆23Updated 7 months ago
- [ICML 2025 Oral] Mixture of Lookup Experts☆27Updated last month
- SQUEEZED ATTENTION: Accelerating Long Prompt LLM Inference☆47Updated 7 months ago
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆39Updated last year
- [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization☆37Updated 9 months ago
- Official Implementation of FastKV: KV Cache Compression for Fast Long-Context Processing with Token-Selective Propagation☆20Updated last month
- [ICLR 2025] TidalDecode: A Fast and Accurate LLM Decoding with Position Persistent Sparse Attention☆39Updated 2 months ago
- [ACL 2024] RelayAttention for Efficient Large Language Model Serving with Long System Prompts☆40Updated last year
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆61Updated 2 months ago
- AFPQ code implementation☆21Updated last year
- Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"☆36Updated 3 weeks ago
- ☆22Updated 7 months ago
- Quantized Attention on GPU☆44Updated 7 months ago
- Source code of paper ''KVSharer: Efficient Inference via Layer-Wise Dissimilar KV Cache Sharing''☆25Updated 8 months ago
- [ICML 2024] When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models☆31Updated last year
- This repo contains the source code for: Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs☆38Updated 10 months ago
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆71Updated 8 months ago
- Official code for the paper "Examining Post-Training Quantization for Mixture-of-Experts: A Benchmark"☆20Updated 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
- Beyond KV Caching: Shared Attention for Efficient LLMs☆19Updated 11 months ago
- More Tokens, Lower Precision: Towards the Optimal Token-Precision Trade-off in KV Cache Compression☆11Updated 5 months ago
- [ICML 2025] SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models☆32Updated 10 months ago
- ☆51Updated 3 months ago
- [ICLR 2024] Jaiswal, A., Gan, Z., Du, X., Zhang, B., Wang, Z., & Yang, Y. Compressing llms: The truth is rarely pure and never simple.☆24Updated 2 months ago
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆38Updated last year
- An unofficial implementation of "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆35Updated last year
- ☆23Updated 2 months ago
- D^2-MoE: Delta Decompression for MoE-based LLMs Compression☆48Updated 3 months ago
- The official implementation of paper: SimLayerKV: A Simple Framework for Layer-Level KV Cache Reduction.☆46Updated 8 months ago