> ## Documentation Index
> Fetch the complete documentation index at: https://docs.gpuhub.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Introduction
> Welcome to the GPUhub documentation. This is the go-to resource for researchers and developers working with GPU-accelerated computing. Get clear, accurate, step-by-step guides to train, deploy, and optimize faster.
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“Do. Or do not. There is no try.” ― Yoda
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## Create Your Container Instance
Create a stable, reliable, and reasonably priced cloud container instance suitable for your use.
Quickly register and create a Cloud Container Instance by selecting the billing model, host, GPU count, and image.
Select the right GPU for your tasks. The platform provides proportional CPU and memory resources based on the number of GPUs selected.
Ensure your programs run continuously in the background when using SSH or SSH-based tools by running commands in daemon mode.
Understand the data retention rules to avoid data loss, especially during instance shutdowns.
## Data Transmission & Storage
We are offering multiple flexible methods for data transfer. It supports various tools and techniques, including JupyterLab, scp commands, and graphical interfaces like FileZilla or XShell, providing users with convenient options for uploading and downloading data.
Ideal for intensive tasks, offering flexible and cost-effective storage solutions.
Perfect for long-term storage and backup, allowing you to manage data without running an instance.
Use various tools like JupyterLab, scp commands, or graphical interfaces for efficient data uploads.
Easily retrieve your data using file transfer tools, terminal commands, or intuitive interfaces.
## Enviroment Configuration
The platform's images come with many frameworks and versions. If they don't meet your needs, see how to configure other versions.
Customize your environment if the pre-installed frameworks and versions don't meet your needs.
Save and reuse custom environments by saving images, or share them with other users.
## SSH & Ports
Manage secure instance access and external connectivity with SSH and customizable ports.
Securely access your instance via SSH for remote management, file transfers, debugging, and running commands directly in the container environment.
Expose custom ports to make your applications accessible over the internet, enabling web services, APIs, dashboards, and other external integrations.
## Elastic Deployment
Effortlessly deploy and manage scalable GPU-accelerated applications with intelligent scheduling, rolling updates, and persistent storage — designed for stable, long-running AI workloads.
Learn how to create ReplicaSets, Jobs, or single containers with flexible resource constraints and automatic host matching.
Understand why GPUhub chooses elastic containers over traditional serverless for better stability, lower latency, and real-world AI training/inference needs.