Showing 3061 open source projects for "intelligence"

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  • 1
    Data-Juicer

    Data-Juicer

    Data processing for and with foundation models

    Data-Juicer is an open-source data processing and augmentation framework designed to enhance the quality and diversity of datasets for machine learning tasks. It includes a modular pipeline for scalable data transformation.
    Downloads: 1 This Week
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  • 2
    CodiumAI Cover-Agent

    CodiumAI Cover-Agent

    CodiumAI Cover-Agent: An AI-Powered Tool for Automated Test Generation

    CodiumAI Cover Agent aims to help efficiently increasing code coverage, by automatically generating qualified tests to enhance existing test suites.
    Downloads: 1 This Week
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  • 3
    NGBoost

    NGBoost

    Natural Gradient Boosting for Probabilistic Prediction

    ngboost is a Python library that implements Natural Gradient Boosting, as described in "NGBoost: Natural Gradient Boosting for Probabilistic Prediction". It is built on top of Scikit-Learn and is designed to be scalable and modular with respect to the choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this slide deck.
    Downloads: 1 This Week
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  • 4
    DeepSparse

    DeepSparse

    Sparsity-aware deep learning inference runtime for CPUs

    A sparsity-aware enterprise inferencing system for AI models on CPUs. Maximize your CPU infrastructure with DeepSparse to run performant computer vision (CV), natural language processing (NLP), and large language models (LLMs).
    Downloads: 0 This Week
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  • 5
    sktime

    sktime

    A unified framework for machine learning with time series

    sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation, and forecasting. It comes with time series algorithms and scikit-learn compatible tools to build, tune and validate time series models. Our objective is to enhance the interoperability and usability of the time series analysis ecosystem in its entirety. sktime provides a...
    Downloads: 3 This Week
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  • 6
    Generative AI

    Generative AI

    Sample code and notebooks for Generative AI on Google Cloud

    Generative AI is a comprehensive collection of code samples, notebooks, and demo applications designed to help developers build generative-AI workflows on the Vertex AI platform. It spans multiple modalities—text, image, audio, search (RAG/grounding) and more—showing how to integrate foundation models like the Gemini family into cloud projects. The README emphasises getting started with prompts, datasets, environments and sample apps, making it ideal for both experimentation and...
    Downloads: 11 This Week
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  • 7
    lightning AI

    lightning AI

    The most intuitive, flexible, way for researchers to build models

    Build in days not months with the most intuitive, flexible framework for building models and Lightning Apps (ie: ML workflow templates) which "glue" together your favorite ML lifecycle tools. Build models and build/publish end-to-end ML workflows that "glue" your favorite tools together. Models are “easy”, the “glue” work is hard. Lightning Apps are community-built templates that stitch together your favorite ML lifecycle tools into cohesive ML workflows that can run on your laptop or any...
    Downloads: 11 This Week
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  • 8
    Claude Overlay

    Claude Overlay

    A floating, screen-aware Claude Code chat for Windows

    Claude Overlay is a Windows utility that places a screen-aware Claude Code assistant in a frameless, always-on-top chat window. It captures the active window or every monitor when a message is sent, letting Claude answer questions about visible documents, errors, dashboards, and applications. Because it runs the installed Claude Code CLI through the Agent SDK, it can also read files, execute commands, and edit open work when permissions allow. The interface streams responses, shows tool...
    Downloads: 20 This Week
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  • 9
    GenMedia Creative Studio

    GenMedia Creative Studio

    AI generative media user experience highlighting use of APIs

    GenMedia Creative Studio is a Google Cloud reference application for experimenting with generative media workflows on Vertex AI. It provides a user experience for working with models and APIs such as Gemini, Veo, Imagen, Gemini Image, Gemini TTS, Chirp 3, and Lyria. The project is built to showcase multimodal creation across text, image, video, speech, and music from one deployable interface. It is useful for creators, marketers, developers, and technical teams that want to prototype...
    Downloads: 6 This Week
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  • 10
    Depth Anything 3

    Depth Anything 3

    Recovering the Visual Space from Any Views

    Depth Anything 3 is a research-driven project that brings accurate and dense depth estimation to any input image or video, enabling foundational understanding of 3D structure from 2D visual content. Designed to work across diverse scenes, lighting conditions, and image types, it uses advanced neural networks trained on large, heterogeneous datasets, producing depth maps that reveal scene depth relationships and object surfaces with strong fidelity. The model can be applied to photography,...
    Downloads: 6 This Week
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  • 11
    abogen

    abogen

    Generate audiobooks from EPUBs, PDFs and text with captions

    abogen is a tool designed to generate audiobooks (or speech narrations) from textual sources such as EPUBs, PDFs, or plain text, with synchronized captions. In other words, it automates the pipeline of reading a digital book (or document), converting its text into speech via a TTS engine, and packaging the result into an audiobook format — likely along with timestamped captions or subtitles that align with the spoken audio. This can be very useful for accessibility, content consumption on...
    Downloads: 6 This Week
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  • 12
    plexe

    plexe

    Build a machine learning model from a prompt

    plexe lets you build machine-learning systems from natural-language prompts, turning plain English goals into working pipelines. You describe what you want—a predictor, a classifier, a forecaster—and the tool plans data ingestion, feature preparation, model training, and evaluation automatically. Under the hood an agent executes the plan step by step, surfacing intermediate results and artifacts so you can inspect or override choices. It aims to be production-minded: models can be exported,...
    Downloads: 6 This Week
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  • 13
    UltraRAG

    UltraRAG

    Less Code, Lower Barrier, Faster Deployment

    UltraRAG 2.0 is a low-code, MCP-enabled RAG framework that aims to lower the barrier to building complex retrieval pipelines for research and production. It provides end-to-end recipes—from encoding and indexing corpora to deploying retrievers and LLMs—so users can reproduce baselines and iterate rapidly. The toolkit comes with built-in support for popular RAG datasets, large corpora, and canonical baselines, plus documentation that walks from “quick start” to debugging and case analysis. It...
    Downloads: 6 This Week
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  • 14
    HexStrike AI MCP Agents

    HexStrike AI MCP Agents

    HexStrike AI MCP Agents is an advanced MCP server

    HexStrike AI is an MCP server that lets LLM agents autonomously operate a large catalog of offensive-security tools. Its goal is to bridge “language models” and practical pentest workflows—enumeration, exploitation, vulnerability discovery, and bug bounty reconnaissance—under safe, auditable controls. The server exposes typed tools and guardrails so agent prompts translate to concrete, parameterized actions rather than brittle shell strings. It ships with curated tool adapters, task...
    Downloads: 6 This Week
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  • 15
    Taipy

    Taipy

    Turns Data and AI algorithms into production-ready web applications

    From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape....
    Downloads: 6 This Week
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  • 16
    spaCy models

    spaCy models

    Models for the spaCy Natural Language Processing (NLP) library

    spaCy is designed to help you do real work, to build real products, or gather real insights. The library respects your time, and tries to avoid wasting it. It's easy to install, and its API is simple and productive. spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. Since its release in 2015, spaCy has become an industry...
    Downloads: 6 This Week
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  • 17
    TPOT

    TPOT

    A Python Automated Machine Learning tool that optimizes ML

    Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
    Downloads: 6 This Week
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  • 18
    OpenDAN

    OpenDAN

    OpenDAN is an open source Personal AI OS

    OpenDAN is an open-source Personal AI OS , that consolidates various AI modules in one place for your personal use. The goal of OpenDAN (Open and Do Anything Now with AI) is to create a Personal AI OS , which provides a runtime environment for various Al modules as well as protocols for interoperability between them. With OpenDAN, users can securely collaborate with various AI modules using their private data to create powerful personal AI agents, such as butlers, lawyers, doctors, teachers,...
    Downloads: 6 This Week
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  • 19
    Ludwig AI

    Ludwig AI

    Low-code framework for building custom LLMs, neural networks

    Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed),...
    Downloads: 6 This Week
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  • 20
    Dream Textures

    Dream Textures

    Stable Diffusion built-in to Blender

    Create textures, concept art, background assets, and more with a simple text prompt. Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. Create textures, concept art, and more with text prompts. Learn how to use the various configuration options to get exactly what...
    Downloads: 6 This Week
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  • 21
    AIMET

    AIMET

    AIMET is a library that provides advanced quantization and compression

    Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware...
    Downloads: 6 This Week
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  • 22
    PyTorch Ignite

    PyTorch Ignite

    Library to help with training and evaluating neural networks

    High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Less code than pure PyTorch while ensuring maximum control and simplicity. Library approach and no program's control inversion. Use ignite where and when you need. Extensible API for metrics, experiment managers, and other components. The cool thing with handlers is that they offer unparalleled flexibility (compared to, for example, callbacks). Handlers can be any function: e.g....
    Downloads: 6 This Week
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  • 23
    Cheshire Cat AI

    Cheshire Cat AI

    AI agent microservice

    Cheshire Cat AI Core is an open-source framework for building customizable AI agents as scalable microservices, designed to integrate conversational intelligence into applications through an API-first architecture. It allows developers to create advanced AI assistants that can interact through WebSockets, REST APIs, and embedded chat interfaces, making it suitable for both backend services and user-facing applications. The framework includes built-in support for retrieval-augmented generation using vector databases such as Qdrant, enabling agents to incorporate external knowledge and documents into their responses. ...
    Downloads: 8 This Week
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  • 24
    Chitu

    Chitu

    High-performance inference framework for large language models

    Chitu is a high-performance inference engine designed to deploy and run large language models efficiently in production environments. The framework focuses on improving efficiency, flexibility, and scalability for organizations that need to run LLM inference workloads across different hardware platforms. It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations....
    Downloads: 8 This Week
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  • 25
    CUDA Agent

    CUDA Agent

    Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

    CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment,...
    Downloads: 0 This Week
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