remote-training

What problem does it solve?

Nebius-based remote training infrastructure coordination is often manual and error-prone, making it difficult to manage Docker images, VM lifecycles, datasets, and end-to-end training/inference workflows.

Core Features & Use Cases

• Docker image management for training environments (build, push, and version control)
• VM lifecycle control (start, stop, restart) for train, train2, train3
• Run training jobs, manage datasets, and monitor progress
• Deploy and operate inference servers for trained models across multiple contexts

Quick Start

Start a Nebius VM, build and push a Docker image, and run a sample training job.