HexanetAI
  • Introduction
  • Tokenomics
  • Roadmap
  • KEY FEATURES
    • GPU Rentals (HexaGPU)
      • Access with SSH
    • Terminal Creator (HexaTermial)
    • AI Wallet (HexaWallet)
    • AI Project Tools (HexaTools)
    • Private VPN (HexaVPN)
    • GPU Cloud gaming (HexaCloudGaming)
    • Train ML Models (HexaTune)
    • AI Cloud (HexaCloud)
    • ML Marketplace (HexaMarket)
    • AI Agents (HexaAgents)
    • ML Models (HexaModels)
    • GPU Node(HexaNode)
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  • Key Features
  • Use Cases
  1. KEY FEATURES

AI Cloud (HexaCloud)

HexaCloud is a versatile cloud environment for managing, deploying, and testing machine learning models. With tools for live preview, API access, SDK integration, and one-click deployment, HexaCloud streamlines the ML model lifecycle, especially for integrating open-source models with ease.


Key Features

  • Model Management and Deployment

    • Comprehensive environment to manage and deploy ML models quickly.

    • Supports seamless integration with a variety of open-source models.

    • One-click deployment simplifies setting up and integrating models for production.

  • Testing and Live Preview

    • Test models directly within HexaCloud’s environment to refine and optimize them.

    • View real-time model performance and predictions with live preview features.

    • Useful for evaluating model outputs before full-scale deployment.

  • API and SDK Integration

    • Provides APIs and SDKs for easy integration into applications.

    • Simplifies connecting models with web apps, mobile apps, or backend systems.

    • Documentation and support included for hassle-free integration.

  • One-Click Open-Source Model Integration

    • Select from a range of popular open-source models and deploy with a single click.

    • Ideal for rapid prototyping and experimentation with established model architectures.


Use Cases

  • Rapid Prototyping: Quickly deploy and test models using the one-click feature to explore project feasibility.

  • Seamless Integration: Use APIs and SDKs to embed models into applications for end-to-end solutions.

  • Model Optimization: Evaluate model performance with live preview, making adjustments before production.

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Last updated 5 months ago