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Showing 152 open source projects for "kernel-br"
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TN 365 KDE Essentials
TechNews365 OS – KDE Edition (EFI Universal)
...Support : 📩 contact@technews365.fr 🌐 https://technews365.fr/contact ✔ Base : Ubuntu/Mint modifiée TechNews365 ✔ Environnement : KDE optimisé ✔ Support EFI corrigé (boot universel) ✔ Compatible VirtualBox / VMware / QEMU ✔ Système stable, rapide et moderne ✔ ISO optimisée pour tests VM et installation réelle 🟩 Mise à jour du système TechNews365 KDE supporte les mises à jour complètes via APT : sudo apt update sudo apt upgrade Le système est basé sur Ubuntu/Mint et KDE , entièrement propre et compatible avec les dépôts officiels. Toutes les mises à jour de sécurité, kernel, pilotes, MINT- KDE et applications système sont supportées. -
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xLaDe
A Lean 4 Ecosystem Framework!
...It is not a theorem library, a fork of Lean, or a replacement for any existing tool. It is an ecosystem layer — a controlled environment for running experiments on how Lean is used, enforcing architectural boundaries that prevent kernel drift, and recording enough metadata to reproduce any experiment correctly, years later. xLaDe is built primarily as a command-line tool for Linux, with tested support for Windows (via WSL) and Android (via Termux). It installs through pip, ships with a comprehensive test suite and remains experimental. -
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ipytest
Pytest in IPython notebooks
ipytest allows you to run Pytest in Jupyter notebooks. ipytest aims to give access to the full pytest experience and to make it easy to transfer tests out of notebooks into separate test files. -
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GrainSizeTools script
A Python script for estimating the grain size from thin sections
Homepage & docs: http://marcoalopez.github.io/GrainSizeTools/ GrainSizeTools is a free, open-source, cross-platform script written in Python that provides several tools for (1) estimating average grain size in polycrystalline materials, (2) characterizing the nature of the distribution of grain sizes (either from apparent distributions or approximating 3D grain size distributions via stereology), and estimating differential stress via paleopizometers. The script requires as the input the... -
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Coq Jupyter
Jupyter kernel for Coq
Make sure that CoqIDE (8.6 or newer) is installed and coqidetop or coqidetop.opt (coqtop for Coq versions before 8.9.0) is in your PATH. Also, make sure the python command is recognized on your machine. If not you can set up an alias for it e.g. python-is-python3 on Ubuntu. There are a number of convenience improvements over standard Jupyter notebook behavior that are implemented to support Coq-specific use cases. -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Kernel evaluation is highly optimized for speed and memory, and computations can be automatically distributed across accelerators with near-linear scaling. -
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Br-Gogo is a Brazilian open-source version of the Gogo Board project. Developed by CTI, a Brazilian research center. **<div class="sf-root" data-id="250926" data-badge="oss-users-love-us-white" style="width:125px"> <a href="https://sourceforge.net/projects/br-gogo/" target="_blank">Br-Gogo</a> </div>**
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GPT-Code UI
An open source implementation of OpenAI's ChatGPT Code interpreter
An open source implementation of OpenAI's ChatGPT Code interpreter. Simply ask the OpenAI model to do something and it will generate & execute the code for you. You can put a .env in the working directory to load the OPENAI_API_KEY environment variable. For Azure OpenAI Services, there are also other configurable variables like deployment name. See .env.azure-example for more information. Note that model selection on the UI is currently not supported for Azure OpenAI Services. -
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linux-factory
Framework used to create custom debian linux operating systems
linux-factory is a utility designed to streamline the process of building and customizing Linux kernel images using a simple, scriptable environment. It provides a modular framework for configuring kernel options, applying patches, and generating bootable images, making it ideal for embedded developers, kernel hackers, and OS maintainers. With a strong emphasis on repeatability and automation, linux-factory reduces the manual overhead of compiling and deploying Linux kernels across various platforms. -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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ConvNeXt
Code release for ConvNeXt model
ConvNeXt is a modernized convolutional neural network (CNN) architecture designed to rival Vision Transformers (ViTs) in accuracy and scalability while retaining the simplicity and efficiency of CNNs. It revisits classic ResNet-style backbones through the lens of transformer design trends—large kernel sizes, inverted bottlenecks, layer normalization, and GELU activations—to bridge the performance gap between convolutions and attention-based models. ConvNeXt’s clean, hierarchical structure makes it efficient for both pretraining and fine-tuning across a wide range of visual recognition tasks. It achieves competitive or superior results on ImageNet and downstream datasets while being easier to deploy and train than transformers. ... -
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m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase... -
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ML workspace
All-in-one web-based IDE specialized for machine learning
...This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. Usable as remote kernel (Jupyter) or remote machine (VS Code) via SSH. Easy to deploy on Mac, Linux, and Windows via Docker. Jupyter, JupyterLab, and Visual Studio Code web-based IDEs.By default, the workspace container has no resource constraints and can use as much of a given resource as the host’s kernel scheduler allows. -
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CommanderPi
Easy RaspberryPi4 GUI system managment
Easy Raspberry Pi 4 GUI system manager. -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network to... -
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Mininet
Emulator for rapid prototyping of Software Defined Networks
...We encourage you to contribute code, bug reports/fixes, documentation, and anything else that can improve the system! Links are virtual ethernet pairs, which live in the Linux kernel and connect our emulated switches to emulated hosts (processes). -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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dumb-init
A minimal init system for Linux containers
...However, omitting an init system often leads to incorrect handling of processes and signals, and can result in problems such as containers that can’t be gracefully stopped, or leaking containers that should have been destroyed. dumb-init is simple to use and solves many of these problems: you can just add it to the front of any container’s command, and it will take on the role of PID 1 for itself. It immediately spawns your process as PID ~2, and then proxies on any signals it receives. This helps to avoid special kernel behavior applied to PID 1, while also handling regular responsibilities of the init system (like reaping orphaned zombie processes). dumb-init is a simple process supervisor and init system designed to run as PID 1 inside minimal container environments (such as Docker). It is deployed as a small, statically-linked binary written in C. -
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BeaEngine 5
BeaEngine disasm project
...You can use it in C/C++ (usable and compilable with Visual Studio, GCC, MinGW, DigitalMars, BorlandC, WatcomC, SunForte, Pelles C, LCC), in assembler (usable with masm32 and masm64, nasm, fasm, GoAsm) in C#, in Python3, in Delphi, in PureBasic and in WinDev. You can use it in user mode and kernel mode. -
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IPython
Command shell for interactive computing in multiple languages
IPython provides a rich toolkit to help you make the most of using Python interactively. Comprehensive object introspection. IPython provides input history, persistent across sessions. Caching of output results during a session with automatically generated references. Extensible tab completion, with support by default for completion of python variables and keywords, filenames and function keywords. Extensible system of ‘magic’ commands for controlling the environment and performing many... -
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BPF Performance Tools
Official repository for the BPF Performance Tools book
BPF Performance Tools Book is the companion repository for Brendan Gregg’s book on Linux performance analysis using eBPF and BCC tracing technologies. The project contains scripts, examples, and reference material that demonstrate how to inspect kernel behavior, application performance, CPU usage, networking activity, file systems, and system bottlenecks in real time. It serves as both an educational resource and a practical toolkit for Linux engineers, SREs, and performance analysts working with modern observability workflows. The repository showcases how eBPF enables safe, low-overhead tracing directly inside the Linux kernel without requiring intrusive instrumentation. ... -
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...https://github.com/SkpyBackup/SkpyBackup Using: https://skpy.t.allofti.me https://pandas.pydata.org https://pypi.org/project/auto-py-to-exe https://visualstudio.microsoft.com/pt-br/vs/community Get this data from your contact list: *id *name *location *language *avatar *mood *phones *birthday *authorised *blocked *favourite
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Coursebook
Introductory Systems Programming Textbook for University of Illinois
...This repository houses a high-quality, open-source introductory systems programming textbook used by the CS 341: System Programming course at the University of Illinois at Urbana-Champaign The book assumes that you have taken a programming language course and are familiar with assembly instructions. All of the code and instruction will be in C, as it is the de-facto language of the Linux Kernel. -
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Drauger OS
Ubuntu-based Linux Gaming OS
...From simple changes such as swapping Gnome out for the light-weight Xfce Desktop Environment and using a dark GTK theme by default, to more complex changes such as using a kernel compiled in-house and replacing PulseAudio with Pipewire. Drauger OS is built from the ground up with our primary focus on performance. DRAUGER OS IS NO LONGER PROVIDED FROM THIS SOURCE. CHECK OUT https://draugeros.org. -
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Nebula Kernel
Nebula Kernel, My Personal Custom Kernel geared towards Performance.
High Performance Kernel that also maintains stability and battery drain to a min.