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  • 1
    UForm

    UForm

    Multi-Modal Neural Networks for Semantic Search, based on Mid-Fusion

    ...This type of models is well-suited for retrieval in large collections. The most famous example of such models is CLIP by OpenAI. Early-fusion models encode both modalities jointly so they can take into account fine-grained features. Usually, these models are used for re-ranking relatively small retrieval results. Mid-fusion models are the golden midpoint between the previous two types. Mid-fusion models consist of two parts – unimodal and multimodal.
    Downloads: 0 This Week
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  • 2
    Jina

    Jina

    Build cross-modal and multimodal applications on the cloud

    ...Seamless Docker container integration: sharing, exploring, sandboxing, versioning and dependency control via Jina Hub. Fast deployment to Kubernetes, Docker Compose and Jina Cloud. Improved engineering efficiency thanks to the Jina AI ecosystem, so you can focus on innovating with the data applications you build.
    Downloads: 0 This Week
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  • 3
    AnnLite

    AnnLite

    A fast embedded library for approximate nearest neighbor search

    ...The library uses a highly optimized approximate nearest neighbor search algorithm (HNSW) to search for nearest neighbors. The library allows you to search for nearest neighbors within a subset of the dataset. Smooth integration with neural search ecosystem including Jina and DocArray, so that users can easily expose search API with gRPC and/or HTTP. The library is easy to install and use. It is designed to be used with Python. To support search with filters, the annlite must be created with colums parameter, which is a series of fields you want to filter by.
    Downloads: 0 This Week
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