Search Results for "tiny core linux" - Page 11
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Showing 435 open source projects for "tiny core linux"
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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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HunterX AI-Assisted Offensive Security Engine Discover. Validate. Prove. Report. HunterX is not merely a vulnerability scanner. It is an open-source, AI-assisted offensive security engine for planning and running authorized security-assessment missions. It combines reconnaissance, security-tool orchestration, AI-assisted reasoning, hypothesis-driven investigation, vulnerability validation, evidence collection, proof / PoC engineering, replay / reproducibility, correlation, impact...
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uweb browser: unlimited power
minimal suckless android web browser with unlimited power
- AI bot as search engine; append file content as input for complex query. - Powerful: html5 enhancement; any urls to host a website; javascript and shell scripting for general processing; and more with Termux. - Customizable: user-defined menus, (new) buttons and gestures for user agents, bookmarklets, url services, shell commands, internal functionality links and text processing etc. - Convenient: book/dictionary/txt/command line/app can be search engine. - Tiny: less than 200k -... -
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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 -
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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... -
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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... -
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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. -
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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... -
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Audiogen Codec
48khz stereo neural audio codec for general audio
AGC (Audiogen Codec) is a convolutional autoencoder based on the DAC architecture, which holds SOTA. We found that training with EMA and adding a perceptual loss term with CLAP features improved performance. These codecs, being low compression, outperform Meta's EnCodec and DAC on general audio as validated from internal blind ELO games. We trained (relatively) very low compression codecs in the pursuit of solving a core issue regarding general music and audio generation, low acoustic... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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... -
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The Hundred-Page Machine Learning Book
The Python code to reproduce illustrations from Machine Learning Book
The Hundred-Page Machine Learning Book is the official companion repository for The Hundred-Page Machine Learning Book written by machine learning researcher Andriy Burkov. The repository contains Python code used to generate the figures, visualizations, and illustrative examples presented in the book. Its purpose is to help readers better understand the concepts explained in the text by allowing them to run and experiment with the underlying code themselves. The book itself provides a... -
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Machine learning basics
Plain python implementations of basic machine learning algorithms
Machine learning basics repository is an educational project that provides plain Python implementations of fundamental machine learning algorithms designed to help learners understand how these methods work internally. Instead of relying on external machine learning libraries, the algorithms are implemented from scratch so that users can explore the mathematical logic and computational structure behind each technique. The repository includes notebooks that demonstrate classic algorithms such... -
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Ai-Learn
The artificial intelligence learning roadmap compiles 200 cases
Ai-Learn is an open-source artificial intelligence learning roadmap that aggregates educational materials, tutorials, and practical projects designed to help beginners study AI and machine learning systematically. The repository was created to help learners start self-study programs in artificial intelligence without getting overwhelmed by the large number of available resources. It organizes topics such as Python programming, mathematics for machine learning, data analysis, deep learning,... -
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OpenPipe
Turn expensive prompts into cheap fine-tuned models
OpenPipe is an open-source platform focused on improving the efficiency and performance of AI systems by transforming expensive prompt-based workflows into optimized, fine-tuned models and reinforcement-trained agents. It provides tools for training language models and agents using real-world feedback, enabling systems to learn from interactions and improve over time rather than relying solely on static prompts. One of its core components, the Agent Reinforcement Trainer, allows developers... -
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Machine Learning for Software Engineers
A complete daily plan for studying to become a machine learning engine
Machine Learning for Software Engineers is an open-source learning roadmap designed to help software engineers transition into machine learning roles through a structured, practical study plan. The repository presents a top-down learning path that emphasizes hands-on experience rather than heavy theoretical prerequisites, making it particularly approachable for developers who already have programming experience but limited formal training in machine learning. The project organizes a... -
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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. -
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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... -
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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... -
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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... -
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DeiT (Data-efficient Image Transformers)
Official DeiT repository
DeiT (Data-efficient Image Transformers) shows that Vision Transformers can be trained competitively on ImageNet-1k without external data by using strong training recipes and knowledge distillation. Its key idea is a specialized distillation strategy—including a learnable “distillation token”—that lets a transformer learn effectively from a CNN or transformer teacher on modest-scale datasets. The project provides compact ViT variants (Tiny/Small/Base) that achieve excellent... -
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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... -
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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),... -
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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... -
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Ubix Linux
The Pocket Datalab
Ubix stands for Universal Business Intelligence Computing System. Ubix Linux is an open-source, Debian-based Linux distribution geared towards data acquisition, transformation, analysis and presentation. Ubix Linux purpose is to offer a tiny but versatile datalab. Ubix Linux is easily accessible, resource-efficient and completely portable on a simple USB key. Ubix Linux is a perfect toolset for learning data analysis and artificial intelligence basics on small to medium datasets. ... -
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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...
