GRIN-MoE

High-performance, low-resource consumption hybrid expert model

PremiumNewProductProgrammingArtificial IntelligenceMachine Learning

GRIN-MoE is a Mixture of Experts (MoE) model developed by Microsoft, focusing on enhancing performance in resource-limited environments. By employing SparseMixer-v2 to estimate the gradient for expert routing, GRIN-MoE achieves model training scalability without relying on expert parallel processing or token dropping, unlike traditional MoE training methods. It excels particularly in coding and mathematical tasks, making it suitable for scenarios that demand strong reasoning capabilities.

Uses SparseMixer-v2 for gradient estimation of expert routing
Scales MoE training without the use of expert parallel processing and token dropping
Performs exceptionally well across various tasks
especially in coding and mathematical applications
Supports multiple languages
with a primary focus on English
Ideal for memory/computationally constrained environments and latency-sensitive applications
Designed to accelerate research in language and multimodal models
serving as a modular component for generative AI capabilities

\The GRIN-MoE model is designed for developers and researchers seeking high-performance AI solutions in resource-constrained environments. It is particularly suited for applications that require processing large volumes of data and performing complex computational tasks while being sensitive to latency.\

In the education sector
it can be used to develop automated programming teaching assistants to help students learn programming and mathematics.
In businesses
it can be utilized to build intelligent search systems for internal knowledge bases
enhancing information retrieval efficiency.

1. Clone the GRIN-MoE GitHub repository to your local environment.
2. Set up the necessary environment and dependencies according to the guidelines in the repository.
3. Download and load the model weights in preparation for inference.
4. Run the command-line or interactive demo and input questions or data for testing.
5. Analyze the model outputs and adjust the model parameters or input data as needed.

Visit

GRIN-MoE Visit Over Time

Monthly Visits

515580771

Bounce Rate

37.20%

Page per Visit

5.8

Visit Duration

00:06:42

GRIN-MoE Visit Trend

GRIN-MoE Visit Geography

GRIN-MoE Traffic Sources

GRIN-MoE Alternatives

SmartDialogue — Explore unlimited intelligence and build a more perfect path of aggregation.

chatting•Artificial Intelligence•Natural Language Processing

510

Mistral-Small-Instruct-2409 — High-performance instruct-tuned AI model

Programming•Artificial Intelligence•Natural Language Processing

xAI — AI to Accelerate Human Scientific Discovery

MemoRAG — A memory-based RAG framework for general-purpose applications

Programming•Natural Language Processing•Machine Learning

RAGLAB — A modular, research-oriented unified framework for retrieval-augmented generation

Programming•Natural Language Processing•Machine Learning

DeepSeek-V2.5 — An AI model integrating general and programming capabilities.

Productivity•Artificial Intelligence•Machine Learning

144

West Lake AI Model — A multimodal model with high emotional and intellectual intelligence

ChineseSelection•Artificial Intelligence•Multimodal

240

RWKV v6 Finch 14B — RWKV v6 Finch 14B is an open-source large model that efficiently processes long texts.

Productivity•Artificial Intelligence•Natural Language Processing

216

C4AI Command R+ 08-2024 — A multilingual advanced dialogue generation model with 104 billion parameters.

Productivity•Artificial Intelligence•Machine Learning

LLM Playground — An interactive platform for loading and testing large language models.

Productivity•Artificial Intelligence•Machine Learning

MiLM-6B — A large-scale pre-trained language model developed by Xiaomi with a parameter scale of 64 billion.

Programming•Natural Language Processing•Machine Learning

252

GPT-4o — GPT-4o, a flagship model capable of real-time processing of audio, visual, and textual data.

chatting•Artificial Intelligence•Natural Language Processing

318

Fugaku-LLM — Fugaku-LLM is an AI model specializing in text generation.

Productivity•Text Generation•Machine Learning

264

Next AI Jobs — Discover the best AI jobs and career opportunities in artificial intelligence, machine learning, natural language processing, and data science.

Business•Artificial Intelligence•Machine Learning

114

MAP-NEO — MAP-NEO is an entirely open-source large language model offering advanced natural language processing capabilities.

Programming•Natural Language Processing•Open Source

426

Amazon Titan Text Premier — An advanced language model designed to build generative AI applications based on Retrieval Augmented Generation (RAG) and agents

Productivity•Artificial Intelligence•Natural Language Processing

234

phi3-Chinese — Committed to collecting and organizing the various training variants of the phi3 model from the open source community, as well as providing tutorials for training, inference, and deployment.

Programming•Artificial Intelligence•Machine Learning

258

spRAG — A Retrieval-Augmented Generation (RAG) framework designed to address challenging queries for dense unstructured data

Programming•Artificial Intelligence•Natural Language Processing

LLaVA++ — LLaVA++ extends the LLaVA model by integrating Phi-3 and LLaMA-3, enhancing the interaction capability between visual and language models.

Programming•Artificial Intelligence•Natural Language Processing

468

Qwen1.5-110B — The first petabyte-scale open-source model in the Qwen1.5 series, supporting multilingual functionality and an efficient Transformer decoder architecture.

ChineseSelection•Artificial Intelligence•Machine Learning

564

Snowflake Arctic — An efficient enterprise-level AI model that achieves high-quality custom models at a low cost.

InternationalSelection•Artificial Intelligence•Machine Learning

168

awesome-prompts — Awesome-prompts is a GitHub repository that collects a variety of useful AI model prompts.

Productivity•Artificial Intelligence•Machine Learning

276

Hugging Face Course — Official courses from Hugging Face, providing tutorials and resources on using Hugging Face products.

Education•Education•Natural Language Processing

834

ReadAgent — A human-inspired reading agent with the capability of remembering key points from very long contexts.

Education•Artificial Intelligence•Natural Language Processing

384

MonkeyLearn — No-code text analytics. Free to start!

Productivity•Machine Learning•Natural Language Processing

636

Claude — Building the future of AI

Productivity•Artificial Intelligence•Deep Learning

708

Best AI Websites & Tools

GRIN-MoE

GRIN-MoE Visit Over Time

GRIN-MoE Visit Trend

GRIN-MoE Visit Geography

GRIN-MoE Traffic Sources

GRIN-MoE Alternatives

O1-Journey — O1 Journey: Strategic Progress Report Part One

Llama-3.2-3B — Multilingual Large Language Model

YunHu Ai — An AI assistant that creates limitless possibilities.

SmartDialogue — Explore unlimited intelligence and build a more perfect path of aggregation.

Mistral-Small-Instruct-2409 — High-performance instruct-tuned AI model

xAI — AI to Accelerate Human Scientific Discovery

MemoRAG — A memory-based RAG framework for general-purpose applications

RAGLAB — A modular, research-oriented unified framework for retrieval-augmented generation

DeepSeek-V2.5 — An AI model integrating general and programming capabilities.

West Lake AI Model — A multimodal model with high emotional and intellectual intelligence

RWKV v6 Finch 14B — RWKV v6 Finch 14B is an open-source large model that efficiently processes long texts.

C4AI Command R+ 08-2024 — A multilingual advanced dialogue generation model with 104 billion parameters.

LLM Playground — An interactive platform for loading and testing large language models.

MiLM-6B — A large-scale pre-trained language model developed by Xiaomi with a parameter scale of 64 billion.

GPT-4o — GPT-4o, a flagship model capable of real-time processing of audio, visual, and textual data.

Fugaku-LLM — Fugaku-LLM is an AI model specializing in text generation.

Next AI Jobs — Discover the best AI jobs and career opportunities in artificial intelligence, machine learning, natural language processing, and data science.

MAP-NEO — MAP-NEO is an entirely open-source large language model offering advanced natural language processing capabilities.

Amazon Titan Text Premier — An advanced language model designed to build generative AI applications based on Retrieval Augmented Generation (RAG) and agents

phi3-Chinese — Committed to collecting and organizing the various training variants of the phi3 model from the open source community, as well as providing tutorials for training, inference, and deployment.

spRAG — A Retrieval-Augmented Generation (RAG) framework designed to address challenging queries for dense unstructured data

LLaVA++ — LLaVA++ extends the LLaVA model by integrating Phi-3 and LLaMA-3, enhancing the interaction capability between visual and language models.

Qwen1.5-110B — The first petabyte-scale open-source model in the Qwen1.5 series, supporting multilingual functionality and an efficient Transformer decoder architecture.

Snowflake Arctic — An efficient enterprise-level AI model that achieves high-quality custom models at a low cost.

awesome-prompts — Awesome-prompts is a GitHub repository that collects a variety of useful AI model prompts.

Hugging Face Course — Official courses from Hugging Face, providing tutorials and resources on using Hugging Face products.

ReadAgent — A human-inspired reading agent with the capability of remembering key points from very long contexts.

MonkeyLearn — No-code text analytics. Free to start!

Claude — Building the future of AI