Showing 355 open source projects for "core gnu/linux"

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  • 1
    Code-Mode

    Code-Mode

    Plug-and-play library to enable agents to call MCP and UTCP tools

    Code-Mode is a plug-and-play library that lets AI agents call tools by executing TypeScript (or via a Python wrapper) instead of making many individual function calls. Its core philosophy is that language models are very good at writing code, so rather than exposing hundreds of separate tool endpoints, you give the model a single “code execution” tool that has access to your full toolkit through code. This approach can dramatically reduce the number of tool-call iterations needed in complex...
    Downloads: 0 This Week
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  • 2
    Raster Vision

    Raster Vision

    Open source framework for deep learning satellite and aerial imagery

    Raster Vision is an open source framework for Python developers building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery). There is built-in support for chip classification, object detection, and semantic segmentation using PyTorch. Raster Vision allows engineers to quickly and repeatably configure pipelines that go through core components of a machine learning workflow: analyzing training data, creating training chips, training...
    Downloads: 0 This Week
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  • 3
    GLM-4.1V

    GLM-4.1V

    GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning

    GLM-4.1V — often referred to as a smaller / lighter version of the GLM-V family — offers a more resource-efficient option for users who want multimodal capabilities without requiring large compute resources. Though smaller in scale, GLM-4.1V maintains competitive performance, particularly impressive on many benchmarks for models of its size: in fact, on a number of multimodal reasoning and vision-language tasks it outperforms some much larger models from other families. It represents a...
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  • 4
    .NET for Apache Spark

    .NET for Apache Spark

    A free, open-source, and cross-platform big data analytics framework

    ...This means you can use .NET for Apache Spark anywhere you write .NET code allowing you to reuse all the knowledge, skills, code, and libraries you already have as a .NET developer. .NET for Apache Spark runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. It also runs on all major cloud providers including Azure HDInsight Spark, Amazon EMR Spark, AWS & Azure Databricks.
    Downloads: 0 This Week
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    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

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  • 5
    MiniMax-01

    MiniMax-01

    Large-language-model & vision-language-model based on Linear Attention

    MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel...
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  • 6
    BotSharp

    BotSharp

    AI Multi-Agent Framework in .NET

    Conversation as a platform (CaaP) is the future, so it's perfect that we're already offering the whole toolkits to our .NET developers using the BotSharp AI BOT Platform Builder to build a CaaP. It opens up as much learning power as possible for your own robots and precisely control every step of the AI processing pipeline. BotSharp is an open source machine learning framework for AI Bot platform builder. This project involves natural language understanding, computer vision and audio...
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  • 7
    MegEngine

    MegEngine

    Easy-to-use deep learning framework with 3 key features

    ...On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference.
    Downloads: 3 This Week
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  • 8
    Deep-Learning-Interview-Book

    Deep-Learning-Interview-Book

    Interview guide for machine learning, mathematics, and deep learning

    Deep-Learning-Interview-Book collects structured notes, Q&A, and concept summaries tailored to deep-learning interviews, turning scattered study into a coherent playbook. It spans the core math (linear algebra, probability, optimization) and the practitioner topics candidates actually face, like CNNs, RNNs/Transformers, attention, regularization, and training tricks. Explanations emphasize intuition first, then key formulas and common pitfalls, so you can reason through unseen questions...
    Downloads: 0 This Week
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  • 9
    Zero to Mastery Deep Learning TensorFlow

    Zero to Mastery Deep Learning TensorFlow

    All course materials for the Zero to Mastery Deep Learning with TF

    This project is a comprehensive, code-first deep learning curriculum built around TensorFlow and Keras, designed to guide learners from foundational concepts to practical model deployment through hands-on experimentation. It is structured as a series of progressively complex Jupyter notebooks that emphasize writing and understanding code before diving into theory, reinforcing learning through repetition and application. The material covers core machine learning workflows including...
    Downloads: 0 This Week
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  • 10
    DeepSeek VL

    DeepSeek VL

    Towards Real-World Vision-Language Understanding

    DeepSeek-VL is DeepSeek’s initial vision-language model that anchors their multimodal stack. It enables understanding and generation across visual and textual modalities—meaning it can process an image + a prompt, answer questions about images, caption, classify, or reason about visuals in context. The model is likely used internally as the visual encoder backbone for agent use cases, to ground perception in downstream tasks (e.g. answering questions about a screenshot). The repository...
    Downloads: 3 This Week
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  • 11
    Luna AI

    Luna AI

    Virtual AI anchor that combines state-of-the-art technology

    Luna AI is a virtual AI streamer framework designed to power an interactive VTuber that can go live on major platforms and chat with viewers in real time. It is built around a core assistant persona called “Luna AI,” which can be driven by a wide range of large language models and platforms, including GPT-style APIs, Claude, LangChain-based backends, ChatGLM, Kimi, Ollama, and many others. The project supports multiple rendering backends for the avatar, such as Live2D, Unreal Engine (UE),...
    Downloads: 4 This Week
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  • 12
    Machine Learning Notebooks

    Machine Learning Notebooks

    Machine Learning Notebooks

    Machine Learning Notebooks is an open-source collection of machine learning notebooks designed to provide practical, minimal, and reusable implementations of common AI tasks across different domains. The project focuses on delivering concise, well-structured Jupyter notebooks that demonstrate how to build, train, and evaluate models using modern machine learning frameworks such as PyTorch. Each notebook is intentionally lightweight, avoiding unnecessary complexity so that users can easily...
    Downloads: 0 This Week
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  • 13
    OneFlow

    OneFlow

    OneFlow is a deep learning framework designed to be user-friendly

    OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous...
    Downloads: 0 This Week
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  • 14
    festival3os

    festival3os

    mods to the Festival sokoban solver to run on OSX + Win + linux

    Mods to the Festival sokoban solver that allow building on OSX, Linux, & Windows
    Downloads: 3 This Week
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  • 15
    Joget

    Joget

    AI Powered Open Source Platform to Easily Build Enterprise Web Apps

    Joget offers an open-source, AI-powered platform that converges no-code/low-code development with AI to rapidly build and customize enterprise applications at scale. By combining AI with visual app builders—not raw code—Joget makes app generation faster, safer, and more accessible for everyone. With Generative AI and Agentic AI capabilities, Joget Intelligence enables organizations to automate and enhance processes while maintaining oversight and compliance. Unlike typical AI code...
    Downloads: 35 This Week
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  • 16
    askimo

    askimo

    AI desktop app with local RAG, privacy-first, multi-model support

    ...The application runs on macOS, Windows, and Linux, with a strong focus on usability, performance, and transparency.
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    Downloads: 11 This Week
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  • 17

    LegacyInsight

    Legacy reverse engineering tool

    LegacyInsight is an AI-powered reverse engineering platform that transforms legacy software systems into comprehensible business logic. Using cutting-edge GenAI, it analyzes legacy and extracts core operations, business rules, and data transformations—all translated into natural language. LegacyInsight supports enterprise-grade systems built on Java, COBOL, NET and other legacy stacks, helping organizations reclaim understanding of business-critical code.
    Downloads: 1 This Week
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  • 18
    PromptSniffer

    PromptSniffer

    View Extract & Remove AI generation metadata with right click

    A powerful tool for reading, extracting, and removing AI generation metadata from image files. Specifically designed to handle metadata from AI image generation tools like ComfyUI, Stable Diffusion, SwarmUI, InvokeAI, and more. Core Functionality Read EXIF/Metadata: Extract and display comprehensive metadata from images AI Metadata Detection: Automatically identify and highlight AI generation metadata Metadata Removal: Strip AI generation metadata while preserving image quality Batch Processing: Handle multiple files with wildcard patterns Cross-Platform: Works on Windows, macOS, and Linux AI Tool Support ComfyUI: Detects and extracts workflow JSON data Stable Diffusion: Identifies prompts, parameters, and generation settings SwarmUI/StableSwarmUI: Handles JSON-formatted metadata Midjourney, DALL-E, NovelAI: Recognizes generation signatures Automatic1111, InvokeAI: Extracts generation parameters
    Downloads: 6 This Week
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  • 19

    phpai

    PHP web application that allows users to interact with AI providers

    Core Features: User Authentication and Management - Secure user registration and login system - API key storage with encryption - User profile management Supported AI Service Integrations: - OpenAI (ChatGPT) - Google Gemini - Anthropic Claude - Mistral AI - Cohere
    Downloads: 0 This Week
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  • 20
    cordum

    cordum

    Enterprise AI Agent Orchestration & Governance Platform.

    Cordum is the infrastructure layer for the Agentic Era. Unlike standard "agent builders," Cordum is an enterprise-grade platform designed to run, manage, and govern AI agents in production at scale. At its core lies the Cordum Agent Protocol (CAP) a high-performance, open standard (NATS/Redis) that decouples agent logic from control. This architecture ensures "Zero-Copy" security (keeping PII off the wire) and provides a centralized Safety Kernel to intercept hallucinations and...
    Downloads: 5 This Week
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  • 21
    dashAI

    dashAI

    dashAI: an interactive platform for training, evaluating and deploying

    dashAI is an open-source, No-code workbench for Exploratory Data Analysis and classical ML. Visual data preparation, multi-model experiments, XAI explainability, and a plugin-based extensible catalog. The platform guides users through a complete, traceable workflow — data ingestion → visual exploration → preprocessing → model training → evaluation → explainability — without writing a single line of code. Each step is explicit and reversible, keeping the user in control rather than...
    Downloads: 5 This Week
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  • 22

    Gemini-Lite

    Lightweight desktop client for Google Gemini built with Rust & Tauri.

    Gemini Lite is an ultra-lightweight, fast, and minimal desktop wrapper for Google's Gemini AI. Built from the ground up using Rust and the Tauri framework, it provides a dedicated desktop chat experience without the massive memory overhead of traditional Electron applications. Instead of bundling a heavy web browser, Gemini Lite cleverly leverages your operating system's native web engine (like Microsoft Edge WebView2 on Windows). This results in a drastically smaller installation size...
    Downloads: 0 This Week
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  • 23
    Hiera

    Hiera

    A fast, powerful, and simple hierarchical vision transformer

    Hiera is a hierarchical vision transformer designed to be fast, simple, and strong across image and video recognition tasks. The core idea is to use straightforward hierarchical attention with a minimal set of architectural “bells and whistles,” achieving competitive or superior accuracy while being markedly faster at inference and often faster to train. The repository provides installation options (from source or Torch Hub), a model zoo with pre-trained checkpoints, and code for evaluation...
    Downloads: 0 This Week
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  • 24
    TypeUI

    TypeUI

    Design system skills for agentic tools

    TypeUI is an open-source CLI tool that provides a unified design layer for AI-generated code across various agentic coding tools. It enables developers to enforce consistent design systems by generating and applying structured design “skills” that guide how UI components are built. These design skills include tokens, styling rules, and layout guidelines that ensure visual consistency regardless of the AI model or tool used. TypeUI works seamlessly with popular AI coding environments like...
    Downloads: 0 This Week
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  • 25
    snorkel

    snorkel

    A system for quickly generating training data with weak supervision

    The Snorkel team is now focusing their efforts on Snorkel Flow, an end-to-end AI application development platform based on the core ideas behind Snorkel. The Snorkel project started at Stanford in 2016 with a simple technical bet: that it would increasingly be the training data, not the models, algorithms, or infrastructure, that decided whether a machine learning project succeeded or failed. Given this premise, we set out to explore the radical idea that you could bring mathematical and...
    Downloads: 0 This Week
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