This handles DeepSpeed's distributed training stack when you're scaling models beyond single GPU limits. You get guidance on ZeRO optimization stages for memory efficiency, pipeline parallelism for splitting models across devices, and mixed precision training with FP16/BF16/FP8. The skill covers DeepNVMe for fast checkpoint I/O to NVMe SSDs using async operations and GPU Direct Storage, plus optimizers like 1-bit Adam for communication reduction. Useful when you're actually implementing multi-GPU training and need to navigate the configuration options or debug memory issues. Generated from Microsoft's official docs, so it tracks their architecture decisions around libaio handles and parallelism patterns.
- skills.sh installs
- 1K
- GitHub stars
- 14.4K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add orchestra-research/ai-research-skills --skill deepspeed --agent claude-codeInstalls into .claude/skills of the current project.
Files
Deepspeed Skill
Comprehensive assistance with deepspeed development, generated from official documentation.
When to Use This Skill
This skill should be triggered when:
- Working with deepspeed
- Asking about deepspeed features or APIs
- Implementing deepspeed solutions
- Debugging deepspeed code
- Learning deepspeed best practices
Quick Reference
Common Patterns
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- Repository
- github.com/orchestra-research/ai-research-skills
- Categories
- DevOps & CI/CD, AI & Agent Building, Data Science & ML, Automation & Workflows, Sales & Marketing
- First seen
- Jun 3, 2026
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