colossal-ai
CommunityAccelerate large model training on domestic AI chips.
Software Engineering#GPU acceleration#distributed training#parallelism#colossalai#large model#AI chip
Authordongg622
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill enables the integration and deployment of Colossal-AI framework for large-scale model training tailored to domestic AI chips, streamlining high-performance computing workflows.
Core Features & Use Cases
- Framework Compatibility: Adapts Colossal-AI to specific hardware like天数智芯 GPUs for scalable training.
- Parallel Modes: Facilitates 3D parallelism, ZeRO, Hybrid Engine, and MoE for efficient resource utilization during training.
- Use Case: Deploy and optimize billion-parameter models on 天数智芯 hardware with minimal manual configuration, supporting scenarios like pretraining, fine-tuning, and inference acceleration.
Quick Start
Use the colossal-ai skill to configure your training environment and run a distributed large model training task efficiently on 天数智芯 hardware.
Dependency Matrix
Required Modules
colossalai
Components
scriptsreferences
💻 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: colossal-ai Download link: https://github.com/dongg622/china-ai-chip-skill/archive/main.zip#colossal-ai Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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