Vanna Labs
  • Introduction
    • 👋Welcome
    • ✨Summary
  • Vision
    • 🏪The AI One-Stop-Shop
      • AI Models on Vanna
      • Applied ML on Vanna
    • 🤝Interoperability
    • ✅Computational Verifiability
    • 🌐Decentralization
    • 🛡️Censorship Resistance
  • Vanna Network
    • 🏗️Architecture
      • Data Preprocessing
      • Parallelized Inference Pre-Execution (PIPE)
      • Validation-Computation Separation (VCS)
      • Cryptoeconomic Security
      • Modular Design
    • ⚙️Inference Modes
      • Vanilla Inference
      • zkML Inference
      • zkFP Inference
      • opML Inference
      • TEE Inference
    • 💿Data Storage
      • Model Storage
      • Data Availability
    • 💻Portal
  • Build
    • 🛠️Getting started
      • Networks
      • Faucets
      • Model Storage
    • 💻Building dApps
      • Data Preprocessing
      • Inference API
      • Inference Example
    • 💾Models
      • Supported LLMs
  • 🔗Links
  • Key Concepts
    • 🧠AI x Blockchain
    • 📜Optimistic Rollups
    • 💾Data Availability
    • ⚡zkML
    • ☀️opML
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Model Storage

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Last updated 1 year ago

The AI/ML models will be stored on Vanna's swarm on IPFS, for accessing the IPFS swarm and connecting to it see the link below.

Storing AI/ML models on a permissionless storage network like IPFS leverages decentralization, mitigating the risk of single points of failure and ensuring model availability even in the absence of centralized servers. This resilience enhances reliability and robustness, a crucial factor for ensuring inference liveness on the Vanna Network.

Moreover, IPFS fosters transparency by enabling easy tracking of model history and versioning, facilitating collaborative development and verification processes. This transparency promotes trust among stakeholders and encourages participation in model improvement and validation efforts. Overall, utilizing IPFS for model storage empowers a more resilient, transparent, and collaborative AI/ML ecosystem that fits Vanna's ethos.

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Model Storage