moe-training
Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse architectures like Mixtral 8x7B or DeepSeek-V3, or scaling model capacity without proportional compute increase. Covers MoE architectures, routing mechanisms, load balancing, expert parallelism, and inference optimization.
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Installation for Agentic Skill
View all platforms →skilz install zechenzhangAGI/AI-research-SKILLs/moe-training skilz install zechenzhangAGI/AI-research-SKILLs/moe-training --agent opencode skilz install zechenzhangAGI/AI-research-SKILLs/moe-training --agent codex skilz install zechenzhangAGI/AI-research-SKILLs/moe-training --agent gemini
First time? Install Skilz: pip install skilz
Works with 14 AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/zechenzhangAGI/AI-research-SKILLs cp -r AI-research-SKILLs/19-emerging-techniques/moe-training ~/.claude/skills/ Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- zechenzhangAGI (GitHub)
- Repository
- AI-research-SKILLs
- Type
- Non-Technical
- Meta-Domain
- general
- Primary Domain
- general
- Sub-Domain
- learning models model
- Market Score
- 27.0
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