Awesome-Mixture-Of-Experts

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awesome-mixture-of-experts is an AI Agents & Automation tool that provides a curated collection of resources related to mixture-of-experts models. It includes papers, code, and other materials for researchers and practitioners.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is awesome-mixture-of-experts?

awesome-mixture-of-experts is a comprehensive GitHub repository dedicated to curating resources on Mixture-of-Experts (MoE) models in deep learning. It serves as a valuable collection of papers, code, and other relevant materials for anyone interested in this advanced AI architecture. The repository is organized into sections covering open models, must-read papers, MoE model publications, MoE system publications, MoE application publications, and libraries. It features prominent MoE models like DeepSeekMoE, LLaMA-MoE, and Mixtral of Experts, alongside foundational and recent research papers. This resource is ideal for researchers, data scientists, and developers looking to explore, understand, and implement MoE models.

Best used for

Ideal for data scientists and researchers who need to quickly access a comprehensive collection of Mixture-of-Experts resources, including papers, code, and open models. Especially valuable for those looking to understand the latest advancements and practical implementations of MoE architectures.

Common actions

research MoE models

find MoE code

explore MoE applications

learn about MoE systems

open-sourceworkflowsgithub copilotautomated workflowdeepfake"AI Agents"collaborationface swappinglow-code/no-code

Capabilities

Key features

Curated MoE papers
MoE code examples
Open MoE models list
MoE system publications
MoE application examples
MoE libraries

Target Audience

data scientistdeveloperstudentprofessor

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What kind of resources are included in awesome-mixture-of-experts?

The repository includes a wide range of resources such as research papers on MoE models, code implementations, lists of open-source MoE models, publications detailing MoE systems, and examples of MoE applications. It also features a section dedicated to essential MoE libraries.

Is awesome-mixture-of-experts suitable for beginners in AI?

While the repository is a comprehensive resource, the content primarily consists of advanced research papers and technical implementations of Mixture-of-Experts models. It is best suited for individuals with a foundational understanding of deep learning and AI concepts.

How frequently is the awesome-mixture-of-experts repository updated?

As an open-source GitHub repository, updates depend on contributions from the maintainer and community. The commit history shows regular additions of new papers and resources, indicating active maintenance to keep the collection current with the latest MoE advancements.

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