model card) 的推出，一种称为混合专家模型 (Mixed Expert Models，简称 MoEs) 的 Transformer 模型在...
MoE,全称为Mixed Expert Models,翻译过来就是混合专家模型。MoE并不是什么最新技术,早在1991年的时候,论文Adaptive Mixture of Local Experts就提出了MoE。 我们知道,模型规模是提升模型性能的关键因素之一,这也是为什么今天的大模型能取得成功。在有限的计算资源预算下,用更少的训练步数训练一个更大的模型,往往比用更...
辅助损失(Auxiliary Loss):辅助损失的引入有助于通过促进专家知识的多样化和提高稀疏门控混合专家模型(sparsely gated mixture-of-expert models)的泛化能力来减少过拟合风险。此外,辅助损失可用于解决特定问题,如专家间的负载平衡或防止专家崩溃,从而进一步提升模型的整体性能。在表2中的实验使用的平衡损失和中使用的路由...
Mixture-of-Experts (MoE)就是这样的一种结构。在训练时,MoE维护多个expert子网络和路由网络。每个expert用于学习和存储来自不同领域的知识,而路由网络根据输入决定本次推理所用到的expert网络。 图2 Transformer MoE结构(图源:Switch Tranformer) 目前,最流行的MoE结构为在transformer层中加入MoE。主流的做法是将transf...
machines, and model compression can reduce the size of expert models without significantly impairing their performance. At inference time, developers can also reduce computational demands by incorporating techniques such as sparsity, which activates only a small subset of experts in response to...
Firstly, a mixture of experts (MoE) model was trained on different physical systems exhibiting these types of nonlinearities. MoE models separate the input space into homogeneous regions and a different expert is responsible for the different regions. In this paper, the experts were low order ...
Sparsely-Gated Mixture-of-Experts layer跟1991年那个工作对比,这里的MoE主要有两个区别: Sparsely-Gated:不是所有expert都会起作用,而是极少数的expert会被使用来进行推理。这种稀疏性,也使得我们可以使用海量的experts来把模型容量做的超级大。 token-level:前面那...
Mixture of experts (MoE) is a machine learning approach, diving an AI model into multiple “expert” models, each specializing in a subset of the input data.
The statistical properties of the likelihood ratio test statistic (LRTS) for mixture-of-expert models are addressed in this paper. This question is essential when estimating the number of experts in the model. Our purpose is to extend the existing results for simple mixture models (Liu and Shao...
就是让不同的 expert 单独计算 loss,然后在加权求和得到总体的 loss。这样的话,每个专家,都有独立判断的能力,而不用依靠其他的 expert 来一起得到预测结果。下面是一个示意图: MoE 在这种设计下,我们将 experts 和 gating network 一起进行训练,最终的系统就会倾向于让一个 expert 去处理一个样本。