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Xmixers: A collection of SOTA efficient token/channel mixers

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Introduction

This repository aims to implement SOTA efficient token/channel mixers. Any technologies related to non-Vanilla Transformer are welcome. If you are interested in this repository, please join our Discord.

Install

Install Torch(>=2.6.0), fla, xopes first, then install xmixers:

git clone https://github.com/Doraemonzzz/xmixers.git
cd xmixers
pip install -e .

Models

Paper Code Config
Elucidating the Design Space of Decay in Linear Attention Link, core code: line 247 to 262. Core method link, Ablation link

Training

To reproduce the results of the paper, we conducted training using the flame framework. First, we configured the environment in accordance with flame's requirements, then used flame's training script, and only needed to replace "config" with the corresponding name.

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Xmixers: A collection of SOTA efficient token/channel mixers

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