uv-deepspeed
CommunityMaster distributed training with DeepSpeed.
Software Engineering#optimization#llm#performance tuning#distributed training#deepspeed#gpu computing
Authoruv-xiao
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides expert guidance and practical examples for leveraging DeepSpeed, a powerful framework for optimizing large-scale deep learning model training, addressing challenges in distributed training, memory efficiency, and scalability.
Core Features & Use Cases
- DeepSpeed Optimization: Understand and implement ZeRO optimization stages, pipeline parallelism, mixed precision (FP16/BF16/FP8), 1-bit Adam, and sparse attention.
- Performance Tuning: Learn how to tune DeepNVMe for optimal I/O performance and configure various DeepSpeed features for maximum efficiency.
- Use Case: You are training a massive language model and encountering out-of-memory errors. This Skill can guide you through configuring DeepSpeed's ZeRO-3 with parameter offloading to CPU/NVMe to fit your model into available hardware.
Quick Start
Use the uv-deepspeed skill to learn about DeepNVMe for data transfers between persistent storage and tensors.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: uv-deepspeed Download link: https://github.com/uv-xiao/pkbllm/archive/main.zip#uv-deepspeed Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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