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emerging-techniques-moe-training — Claude Code skill

Provides guidance and code templates for training Mixture of Experts models with DeepSpeed and Transformers. Scales model capacity without matching compute growth.

Install into Claude Code · claude-code-templates All methods and platforms ↓ 
npx claude-code-templates@latest --skill ai-research/emerging-techniques-moe-training
Open on GitHub

What emerging-techniques-moe-training does

This skill guides developers through implementing sparse Mixture of Experts (MoE) architectures like Mixtral 8x7B or DeepSeek-V3. It helps write custom routing layers and combine outputs from active experts.

The template covers Top-1 and Top-2 routing alongside expert choice mechanisms. To keep the router stable, it details auxiliary balancing loss and router z-loss calculations that prevent tokens from flooding a single expert.

Running the training scripts requires torch, deepspeed, transformers, and accelerate. Without installing these Python packages, distributed execution will fail immediately.

What it helps with

  • build custom PyTorch MoE layers with Top-1 or Top-2 gating
  • implement auxiliary loss terms to balance expert utilization
  • set up DeepSpeed flags for distributed expert parallelism
  • train sparse architectures comparable to Mixtral or DeepSeek-V3

Example prompts for the agent

  • Help me build a custom PyTorch MoE layer with Top-2 gating and auxiliary loss
  • Write a DeepSpeed launch command for pretraining an MoE model with 128 experts

How to install emerging-techniques-moe-training

1claude-code-templates

npx claude-code-templates@latest --skill ai-research/emerging-techniques-moe-training

2Skills CLI (Vercel)

npx skills add davila7/claude-code-templates --skill emerging-techniques-moe-training -a claude-code

3Manually: put the files in place

~/.claude/skills/emerging-techniques-moe-training/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/emerging-techniques-moe-training/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about emerging-techniques-moe-training

How to install emerging-techniques-moe-training in Claude Code?

Run npx claude-code-templates@latest --skill ai-research/emerging-techniques-moe-training in your environment. The template will be installed into your project.

What is the main purpose of this skill?

It assists in designing and training sparse Mixture of Experts architectures, reducing compute demands compared to dense models.

Which dependencies are required to run the code?

Your Python environment must have torch, deepspeed (version 0.6.0 or higher), transformers, and accelerate installed.

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