The rapid advancement of large language models (LLMs) has led to architectures with billions to trillions of parameters, posing significant deployment challenges due to their substantial demands on memory, processing power, and energy c...
Sparse video representation using steered mixture-of-experts with global motion compensationdoi:10.1117/12.2665600VideoMotion modelsEducation and trainingVideo codingImage compressionData modelingVideo compressionImage restorationModelingVideo processingSteered-Mixtures-of-Experts (SMoE) present a unified framework ...
SiRA leverages the Sparse Mixture of Expert(SMoE) to boost the performance of LoRA. Specifically it enforces the top k experts routing with a capacity limit restricting the maximum number of tokens each expert can process. We propose a novel and simple expert dropout on top of gating network ...
SiRA leverages the Sparse Mixture of Expert(SMoE) to boost the performance of LoRA. Specifically it enforces the top k experts routing with a capacity limit restricting the maximum number of tokens each expert can process. We propose a novel and simple expert dropout on top of gating network ...
Triton-based implementation of Sparse Mixture-of-Experts (SMoE) on GPUs. ScatterMoE builds upon existing implementations, and overcoming some of the limitations to improve inference, training speed, and memory footprint. This implementation achieves this by avoiding padding and making excessive copies ...
题目:SEER-MoE: Sparse Expert Efficiency through Regularization for Mixture-of-Experts 名称:SEER-MoE:通过混合专家的正则化提高稀疏专家效率 论文:arxiv.org/abs/2404.0508 代码: 单位:斯坦福、Google、NVIDIA 出版:Arxiv 2024 SparseMoe-Dropout 题目:Sparse MoE as the New Dropout: Scaling Dense and Self-...
Our implementation is based onfastmoe repo,huggingface repoandSmoe-Dropout repo. Citation @inproceedings{ truong2023hyperrouter, title={HyperRouter: Towards Efficient Training and Inference of Sparse Mixture of Experts via HyperNetwork}, author={Truong Giang Do and Le Huy Khiem and TrungTin Nguyen an...
Sparse Views名称：SparseNeuS：从稀疏视图快速通用神经表面重建论文：https://arxiv.org/abs/2206.05737代码：https://github.com/xxlong0/SparseNeuS单位：香港大学、腾讯Game出版：ECCV 202230.SparseMoE/混合专家模型SEER-MoE题目：SEER-MoE: Sparse Expert Efficiency through Regularization for Mixture-of-Experts...
Sparse Views名称：SparseNeuS：从稀疏视图快速通用神经表面重建论文：https://arxiv.org/abs/2206.05737代码：https://github.com/xxlong0/SparseNeuS单位：香港大学、腾讯Game出版：ECCV 202230.SparseMoE/混合专家模型SEER-MoE题目：SEER-MoE: Sparse Expert Efficiency through Regularization for Mixture-of-Experts...