Search Results for "kreatv-kernel-smartlabs.bin"
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Showing 105 open source projects for "kreatv-kernel-smartlabs.bin"
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ShredOS
Shredos Disk Eraser 64 bit for all Intel 64 bit processors
... for new hardware since that date. Nwipe originally was a fork of dwipe but has continued to have improvements and bug fixes and is now available in many Linux distros. ShredOS hopefully will always provide the latest nwipe on a up to date Linux kernel so it will support modern hardware. -
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IPython Kernel for Jupyter
IPython Kernel for Jupyter
This package provides the IPython kernel for Jupyter. IPython provides a rich toolkit to help you make the most of using Python interactively. -
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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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CadQuery
A python parametric CAD scripting framework based on OCCT
... be edited and executed with only a web browser. The scripts use a standard programming language, Python, and thus can benefit from the associated infrastructure. This includes many standard libraries and IDEs. CadQuery's CAD kernel Open CASCADE Technology (OCCT) is much more powerful than the CGAL used by OpenSCAD. Features supported natively by OCCT include NURBS, splines, surface sewing, STL repair, STEP import/export, and other complex operations. -
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CuPy
A NumPy-compatible array library accelerated by CUDA
.... CuPy is very easy to install through pip or through precompiled binary packages called wheels for recommended environments. It also makes writing a custom CUDA kernel very easy, requiring only a small code snippet of C++. -
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Ricks-Lab GPU Utilities
A set of utilities for monitoring and customizing GPU performance
A set of utilities for monitoring GPU performance and modifying control settings. In order to get the maximum capability of these utilities, you should be running with a kernel that provides support for the GPUs you have installed. If using AMD GPUs, installing the latest AMD GPU driver or ROCm package may provide additional capabilities. If you have Nvidia GPUs installed, you should have Nvidia-smi installed in order for the utility reading of the cards to be possible. Writing to GPUs... -
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Jupyter Enterprise Gateway
Enables Jupyter Notebooks to share resources across clusters
... that enables the ability to launch kernels on behalf of remote notebooks. This leads to better resource management, as the web server is no longer the single location for kernel activity. It essentially exposes a Kernel as a Service model. By default, the Jupyter framework runs kernels locally - potentially exhausting the server of resources. By leveraging the functionality of the underlying resource management applications like Hadoop YARN, Kubernetes, and others. -
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Spyder notebook plugin
Jupyter notebook integration with Spyder
Spyder plugin to use Jupyter notebooks inside Spyder. Currently, it supports basic functionality such as creating new notebooks, opening any notebook in your filesystem and saving notebooks at any location. You can also use Spyder's file switcher to easily switch between notebooks and open an IPython console connected to the kernel of a notebook to inspect its variables in the Variable Explorer. -
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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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Qiling
Qiling Advanced Binary Emulation Framework
Cross-platform and multi-arch ultra lightweight emulator. Supported OS: Linux, MacOS, Windows, FreeBSD, DOS and UEFI. Support Arch: x86(16/32/64), ARM(64) MIPS, EVM and WASM. It also support Linux Kernel Module(.ko) , Windows Driver(.sys) and MacOS Kernel(.kext) via Demigod. Binary instrumentation and API are Qiling Framework's main focus and priority. It is designed for reverse engineers - thus there is no need to rebuild another sand boxing tool. Using Qiling Framework saves you time. The API... -
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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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nbmake
Pytest plugin for testing notebooks
Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks. -
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voila
Voilà turns Jupyter notebooks into standalone web applications
From notebooks to standalone web applications and dashboards. Voilà allows you to convert a Jupyter Notebook into an interactive dashboard that allows you to share your work with others. It is secure and customizable, giving you control over what your readers experience. Unlike the usual HTML-converted notebooks, each user connecting to the Voilà tornado application gets a dedicated Jupyter kernel which can execute the callbacks to changes in Jupyter interactive widgets. To render the bqplot... -
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AtomAI
Deep and Machine Learning for Microscopy
AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless... -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
... of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations. -
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CachyOS
Blazingly Fast & Customizable Linux distribution
CachyOS - Arch Linux Based Distribution With Heavy Optimizations & Multi-Architectures For Ultimate Desktop Experience Filesystems: - btrfs - zfs - ext4 - xfs - f2fs Our installer will auto detect which micro architecture your machine got, if x86-64-v3 or x86-64-v4 is detected it will automatically use the optimized packages, which is around a 10 % performance improvement. Desktop Environments: - KDE - CuteFish - i3 - Gnome - Openbox - Wayfire - Xfce - LXQT -... -
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FreeCAD
a parametric 3D CAD modeler
... and customization. FreeCAD is based on OpenCasCade, a powerful geometry kernel, features an Open Inventor-compliant 3D scene representation model provided by the Coin 3D library, and a broad Python API. The interface is built with Qt. FreeCAD runs exactly the same way on Windows, Mac OSX and Linux platforms. -
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CDemu - a virtual CD/DVD drive for Linux. Project includes Linux kernel module & userspace utilities.
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Robolinux
MAX Privacy with Robolinux R12.12
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Linux GPIB Support
Linux GPIB Driver package (source)
The Linux GPIB Package is a support package for GPIB (IEEE 488.2) hardware. The package contains a development environment consisting of a GPIB library written in C, kernel driver modules, and bindings for several other languages. -
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KaNaPi
Educational Linux Distribution
Main goals: * Prepare operating system based on Linux kernel and free software for use at home from scratch by building sources. Binary packages/images are also available. * Each package is installed in separate directory, so you can use different versions of applications and libraries by design. * There is only one user 'kanapi' with root permissions, so you don't have to login, remember passwords, etc. * Simple configuration * Automatic compilation. -
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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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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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Linux-based DIY DCC (Model Railroad Digital Command Control) The project has morphed somewhat from its starting point. There's now a LOT of hardware bits, designed in CadSoft Eagle (V7, not the AutoDesk versions) and low-level code for PIC and ARM embedded micros. The Linux kernel driver for the original hardware is still there but increasingly redundant.
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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