uv-ray-train

What problem does it solve?

This Skill addresses the challenge of scaling machine learning model training from a single machine to large, distributed clusters, simplifying the process of training massive models and performing hyperparameter tuning across multiple nodes.

Core Features & Use Cases

• Distributed Training: Seamlessly scales PyTorch, TensorFlow, and HuggingFace models across multiple GPUs and nodes with minimal code changes.
• Hyperparameter Tuning: Integrates with Ray Tune for efficient, distributed hyperparameter optimization.
• Fault Tolerance & Checkpointing: Automatically handles worker failures and resumes training from saved checkpoints.
• Use Case: Train a large language model on a cluster of 100 GPUs, or run a hyperparameter sweep for a complex deep learning model across 32 nodes.

Quick Start

Use the uv-ray-train skill to scale your PyTorch training script across 4 GPUs.