Models
Datasets
Spaces
Posts
Docs
Pricing
Log In
Sign Up

Collections

Discover the best community collections!

Collections including paper arxiv:2401.06066

Papers - MoE - Training

Robust Mixture-of-Expert Training for Convolutional Neural Networks

Paper • 2308.10110 • Published Aug 19, 2023 • 2
Experts Weights Averaging: A New General Training Scheme for Vision Transformers

Paper • 2308.06093 • Published Aug 11, 2023 • 2
ConstitutionalExperts: Training a Mixture of Principle-based Prompts

Paper • 2403.04894 • Published Mar 7 • 2
Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models

Paper • 2403.03432 • Published Mar 6

Non-asymptotic oracle inequalities for the Lasso in high-dimensional mixture of experts

Paper • 2009.10622 • Published Sep 22, 2020 • 1
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Paper • 2401.15947 • Published Jan 29 • 46
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts

Paper • 2401.04081 • Published Jan 8 • 68
MoE-Infinity: Activation-Aware Expert Offloading for Efficient MoE Serving

Paper • 2401.14361 • Published Jan 25 • 2

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29 • 50
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 135
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16 • 19
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11 • 35

BlackMamba: Mixture of Experts for State-Space Models

Paper • 2402.01771 • Published Feb 1 • 22
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models

Paper • 2402.01739 • Published Jan 29 • 26
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Paper • 2401.15947 • Published Jan 29 • 46
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11 • 35

Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28 • 17
Linear Transformers with Learnable Kernel Functions are Better In-Context Models

Paper • 2402.10644 • Published Feb 16 • 74
Repeat After Me: Transformers are Better than State Space Models at Copying

Paper • 2402.01032 • Published Feb 1 • 22
Zoology: Measuring and Improving Recall in Efficient Language Models

Paper • 2312.04927 • Published Dec 8, 2023 • 2

BlackMamba: Mixture of Experts for State-Space Models

Paper • 2402.01771 • Published Feb 1 • 22
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models

Paper • 2402.01739 • Published Jan 29 • 26
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11 • 35

Mixture of Experts Papers

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Paper • 2401.15947 • Published Jan 29 • 46
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11 • 35
SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention

Paper • 2312.07987 • Published Dec 13, 2023 • 39
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

Paper • 2101.03961 • Published Jan 11, 2021 • 13

Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Paper • 2401.09417 • Published Jan 17 • 51
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts

Paper • 2401.04081 • Published Jan 8 • 68
SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention

Paper • 2312.07987 • Published Dec 13, 2023 • 39
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11 • 35

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 135
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17 • 27
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16 • 19
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10 • 62

mixture-of-experts

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Paper • 1701.06538 • Published Jan 23, 2017 • 4
Sparse Networks from Scratch: Faster Training without Losing Performance

Paper • 1907.04840 • Published Jul 10, 2019 • 3
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

Paper • 1910.02054 • Published Oct 4, 2019 • 3
A Mixture of h-1 Heads is Better than h Heads

Paper • 2005.06537 • Published May 13, 2020 • 2

Previous
1
2
3
Next

Company

© Hugging Face

TOS Privacy About Jobs

Website

Models Datasets Spaces Pricing Docs