Showing 7 open source projects for "vector"

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  • 1
    SuperDuperDB

    SuperDuperDB

    Integrate, train and manage any AI models and APIs with your database

    Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. ...
    Downloads: 0 This Week
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  • 2
    Embedding Studio

    Embedding Studio

    Framework which allows you transform your Vector Database

    Embedding Studio is a framework that transforms vector databases into feature-rich search engines. It leverages embeddings to enhance search capabilities, enabling more accurate and context-aware retrieval of information. Embedding Studio supports various data types and integrates seamlessly with existing databases, providing tools for fine-tuning and optimizing embeddings to suit specific application needs.
    Downloads: 0 This Week
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  • 3
    UForm

    UForm

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

    UForm is a Multi-Modal Modal Inference package, designed to encode Multi-Lingual Texts, Images, and, soon, Audio, Video, and Documents, into a shared vector space! It comes with a set of homonymous pre-trained networks available on HuggingFace portal and extends the transfromers package to support Mid-fusion Models. Late-fusion models encode each modality independently, but into one shared vector space. Due to independent encoding late-fusion models are good at capturing coarse-grained features but often neglect fine-grained ones. ...
    Downloads: 0 This Week
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  • 4
    DeepCamera

    DeepCamera

    Open-Source AI Camera. Empower any camera/CCTV

    ...SharpAI yolov7_reid is an open-source Python application that leverages AI technologies to detect intruders with traditional surveillance cameras. The source code is here It leverages Yolov7 as a person detector, FastReID for person feature extraction, Milvus the local vector database for self-supervised learning to identify unseen persons, Labelstudio to host images locally and for further usage such as label data and train your own classifier. It also integrates with Home-Assistant to empower smart homes with AI technology.
    Downloads: 4 This Week
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  • 5
    marqo

    marqo

    Tensor search for humans

    A tensor-based search and analytics engine that seamlessly integrates with your applications, websites, and workflows. Marqo is a versatile and robust search and analytics engine that can be integrated into any website or application. Due to horizontal scalability, Marqo provides lightning-fast query times, even with millions of documents. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. It can seamlessly handle image-to-image, image-to-text and...
    Downloads: 0 This Week
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  • 6
    Infinity

    Infinity

    Low-latency REST API for serving text-embeddings

    Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. Infinity is developed under MIT License. Infinity powers inference behind Gradient.ai and other Embedding API providers.
    Downloads: 5 This Week
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  • 7
    Superduper

    Superduper

    Superduper: Integrate AI models and machine learning workflows

    Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. ...
    Downloads: 0 This Week
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