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4 个仓库

Awesome GitHub RepositoriesVector Index Compression

Techniques for converting high-precision vectors into compact forms to reduce memory footprint and latency.

Distinct from Vector Indexing: Specifically addresses the compression of vectors for memory efficiency, whereas the parent is general indexing management.

Explore 4 awesome GitHub repositories matching data & databases · Vector Index Compression. Refine with filters or upvote what's useful.

Awesome Vector Index Compression GitHub Repositories

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  • facebookresearch/parlaifacebookresearch 的头像

    facebookresearch/ParlAI

    10,625在 GitHub 上查看↗

    ParlAI is a conversational AI research framework designed for training, evaluating, and sharing dialogue models using a unified interface for datasets and agents. It functions as a PyTorch-based training platform and a dialogue data collection system, providing a centralized model zoo for the distribution of versioned pretrained agents. The project distinguishes itself through a knowledge-grounded retrieval system that combines dense and sparse indexing to ground responses in external information. It also provides a comprehensive infrastructure for gathering human-AI interaction data via inte

    Utilizes compressed embeddings within FAISS indices to optimize memory usage and speed up passage retrieval.

    Python
    在 GitHub 上查看↗10,625
  • alibaba/zvecalibaba 的头像

    alibaba/zvec

    5,198在 GitHub 上查看↗

    zvec is an embedded vector database engine and indexing library designed for high-dimensional similarity search. It functions as a hybrid search engine and a retrieval-augmented generation knowledge base, allowing for the storage and retrieval of dense and sparse vectors. The system is distinguished by its hybrid retrieval pipeline, which fuses vector similarity, full-text keyword matching, and scalar metadata filtering into single query operations. It supports a plugin-based model integration system for registering custom embedding models and rerankers, as well as language bindings for nativ

    Converts high-precision vectors into compact forms to reduce memory usage and lower query latency.

    C++ann-searchembedded-databaserag
    在 GitHub 上查看↗5,198
  • answerdotai/ragatouilleAnswerDotAI 的头像

    AnswerDotAI/RAGatouille

    3,937在 GitHub 上查看↗

    RAGatouille 是一个检索框架和搜索引擎,旨在实现和训练后期交互 (late-interaction) 检索模型。它作为生成式 AI 流水线的模块化检索组件,专注于高性能文档排序以提高搜索准确性。 该项目提供了一个使用对和三元组训练及微调检索模型的工具包,具有用于领域适应的自动硬负样本挖掘功能。它实现了一种后期交互机制,通过利用压缩嵌入在检索速度和精度之间取得平衡。 该系统涵盖了文档索引和检索操作,利用基于磁盘的向量存储来处理超出可用系统内存的数据集。它进一步支持通过映射标记级嵌入来创建检索增强生成工作流,以保留细粒度的语义信息。

    Implements quantized vector storage to reduce memory footprint and latency during retrieval.

    Python
    在 GitHub 上查看↗3,937
  • unum-cloud/usearchunum-cloud 的头像

    unum-cloud/USearch

    3,888在 GitHub 上查看↗

    USearch is a high-performance vector similarity search engine and approximate nearest neighbor index designed for dense embeddings. It functions as a low-level vector database core and high-dimensional vector indexer, providing the primitives necessary to store and retrieve vectors across massive datasets. The engine distinguishes itself through hardware-level SIMD acceleration for distance kernels and a proximity-graph indexing system that enables fast retrieval across billions of vectors. It supports multi-precision vector quantization to balance memory usage and accuracy, and utilizes memo

    Reduces memory footprint by storing vectors as half-precision floats, 8-bit integers, or packed binary formats.

    C++approximate-nearest-neighbor-searchclusteringdatabase
    在 GitHub 上查看↗3,888
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