ray-distributed-sft
CommunityEffortless multi-GPU supervised fine-tuning across nodes with Ray
Authorhung-phan
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Handles large-scale supervised fine-tuning (SFT) across multiple GPUs or nodes, addressing limitations of single-GPU setups and providing fault tolerance.
Core Features & Use Cases
- Multi-GPU Training: Scale your SFT from a single GPU to multi-node setups.
- Fault Tolerance: Automated restarts on worker failures and cloud-native checkpoint storage.
- Use Case: Ideal for scenarios where your model or dataset is too large for a single GPU, or you require fault-tolerant distributed training.
Quick Start
Execute the Ray Distributed SFT script with the provided configuration file to initiate multi-GPU training.
Dependency Matrix
Required Modules
rayray.traindeepspeedtransformerstrl
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: ray-distributed-sft Download link: https://github.com/hung-phan/ml-skills/archive/main.zip#ray-distributed-sft Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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