RedShadowAI

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⚔️ RedShadowAI

Pushing the boundaries of Sparse Mixture-of-Experts (MoE) architectures, expert routing, and efficient inference.

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⚔️ Overview

RedShadowAI is an open-source AI collective dedicated to designing, merging, and fine-tuning high-capacity Sparse Mixture-of-Experts (MoE) systems.

Our core research focuses on decoupling total parameter capacity from per-token compute costs. By dynamically routing tokens to specialized subnetworks, our architectures maintain massive parameter efficiency—activating only a lightweight fraction of the network during forward passes to deliver low latency and accessible hardware footprints.


⚡ What We Build

  • Sparse MoE Checkpoints: Standalone, deep MoE architectures built via advanced routing matrices, continuous pretraining, and structural merges.
  • LoRA & QLoRA Expert Adapters: Modular, parameter-efficient adapters trained on specialized domains (reasoning, code, structured deliberation) designed to drop directly into supported MoE base models.
  • Specialized Routing Implementations: Research into gating mechanics, expert load-balancing, and loss-minimized routing heuristics.

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