Showing 4 open source projects for "support vector machine"

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  • 1
    Aix-DB

    Aix-DB

    Based on the LangChain/LangGraph framework

    ...The platform supports multiple types of data sources and provides an end-to-end pipeline that includes intent recognition, SQL generation, database execution, and visual presentation of results. Its architecture includes multiple layers such as a web interface, API gateway, AI service layer, and data storage layer that support relational databases, vector stores, graph databases, and file systems.
    Downloads: 1 This Week
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  • 2
    AnythingLLM

    AnythingLLM

    The all-in-one Desktop & Docker AI application with full RAG and AI

    A full-stack application that enables you to turn any document, resource, or piece of content into a context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions. AnythingLLM is a full-stack application where you can use commercial off-the-shelf LLMs or popular open-source LLMs and vectorDB solutions to build a private ChatGPT with no...
    Downloads: 153 This Week
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  • 3
    Lemon AI

    Lemon AI

    Full-stack Open-source Self-Evolving General AI Agent

    LemonAI is an open-source full-stack framework for building autonomous AI agents capable of performing complex tasks such as research, programming, data analysis, and document processing. The platform is designed to run primarily on local infrastructure, providing a privacy-focused alternative to cloud-dependent agent platforms. It integrates with local large language models through tools such as Ollama, vLLM, and other model runtimes while also allowing optional connections to external...
    Downloads: 3 This Week
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  • 4
    Transformer Explainer

    Transformer Explainer

    Learn How LLM Transformer Models Work with Interactive Visualization

    Transformer Explainer is an interactive visualization tool created to help users understand how transformer-based language models operate internally. The platform runs a lightweight GPT-2 model directly in the user’s browser and allows users to experiment with text prompts while observing the model’s internal operations. Through visual diagrams and interactive interfaces, the tool reveals how tokens are processed through layers such as embeddings, attention mechanisms, and feed-forward...
    Downloads: 2 This Week
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