THub Technical Documentation
  • Introduction
  • 🔗 LangChain
    • 🕵️ Agents
    • 🗄️Cache
    • ⛓️Chains
    • 🗨️Chat Models
    • 📁Document Loaders
    • 🧬Embeddings
    • 🧠Large Language Models(LLM)
    • 💾Memory
    • 🛡️Moderation
    • 👥Multi Agents
    • 🔀Output Parsers
    • 📝Prompts
    • 📊Record Managers
    • 📑Retrieval-Augmented Generation
    • 🔍Retrivers
    • ✂️Text Splitters
    • 🛠️Tools
    • 🔌Utilities
    • 🗃️Vector Stores
  • 🦙LLama Index
    • 🕵️ Agents
    • 🗨️Chat Models
    • 🧬Embeddings
    • 🚀Engine's
    • 🧪Response Synthesizer
    • 🛠️Tools
    • 🗃️Vector Stores
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  1. 🦙LLama Index

🧬Embeddings

Embeddings can be used to create a numerical representation of textual data. This numerical representation is useful because it can be used to find similar documents.

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Last updated 10 months ago

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Embeddings