SkillCheatSheet
moe-training
An AI agent skill from Orchestra-Research/AI-Research-SKILLs, scored 55 out of 100 by code.
Code score by group
It loses the most points in Done criteria (15), the group that checks whether there is a checklist and a step that verifies the work.
What the author says it does
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.
This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.
- Repository
- Orchestra-Research/AI-Research-SKILLs
- Folder
- 19-emerging-techniques/moe-training
- License
- MIT
- GitHub stars
- 14,480
- SKILL.md lines
- 527
- Other files
- 3
Add moe-training to your agent
npx skills add Orchestra-Research/AI-Research-SKILLs --skill moe-trainingThe command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.
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Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.