Search Results for "unix utilities for windows"
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Showing 83 open source projects for "unix utilities for windows"
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User Testing Platform | TesteumTired of bugs and poor UX going unnoticed despite thorough internal testing? Testeum is the SaaS crowdtesting platform that connects mobile and web app creators with carefully selected testers based on your criteria.
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Accounting Software for Small Businesses | XeroXero offers a robust ecosystem of connected apps and integrations with banks and financial institutions, enabling small businesses to access a wide range of solutions within Xero's open platform to streamline operations and manage finances. Additionally, accounting and bookkeeping firms benefit from efficient compliance tools, advanced practice management software, and a cloud-based unified accounting ledger for all clients, centralized in one place.
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High-Level Training Utilities Pytorch
High-level training, data augmentation, and utilities for Pytorch
Contains significant improvements, bug fixes, and additional support. Get it from the releases, or pull the master branch. This package provides a few things. A high-level module for Keras-like training with callbacks, constraints, and regularizers. Comprehensive data augmentation, transforms, sampling, and loading. Utility tensor and variable functions so you don't need numpy as often. Have any feature requests? Submit an issue! I'll make it happen. Specifically, any data augmentation, data... -
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Coqui TTS
A deep learning toolkit for Text-to-Speech, battle-tested in research
... efficiently. Vocoder models (MelGAN, Multiband-MelGAN, GAN-TTS, ParallelWaveGAN, WaveGrad, WaveRNN) Fast and efficient model training. Detailed training logs on the terminal and Tensorboard. Support for Multi-speaker TTS. Efficient, flexible, and lightweight but feature complete Trainer API. Released and ready-to-use models. Tools to curate Text2Speech datasets underdataset_analysis. Utilities to use and test your models. -
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Cline
Autonomous coding agent right in your IDE
Cline is a command-line application building library for Node.js that helps developers easily create interactive CLI applications. Built on Node's readline module, it offers features like history support, auto-completion, and input masking. Cline allows you to define custom commands with argument placeholders, making it versatile for various command structures. Additionally, it supports modes, where different command sets can be dynamically loaded depending on the application's state. -
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Pedalboard
A Python library for audio
pedalboard is a Python library for working with audio: reading, writing, rendering, adding effects, and more. It supports the most popular audio file formats and a number of common audio effects out of the box and also allows the use of VST3® and Audio Unit formats for loading third-party software instruments and effects. pedalboard was built by Spotify’s Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. Internally at Spotify, pedalboard... -
Enterprise and Small Business CRM Solution | Clear C2 C2CRMC2CRM consists of four modules that integrate to provide a comprehensive CRM solution: Relationship Management, Sales Automation, Marketing Automation, and Customer Service. Only buy what each user needs.
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Ninjabot
A fast cryptocurrency platform for trading bot in Go
A fast cryptocurrency trading bot framework implemented in Go. Ninjabot permits users to create and test custom strategies for spot markets. Ninjabot is an open-source platform that provides tools to implement custom strategies and backtests for trading cryptocurrencies in Go. Ninjabot CLI provides utilities commands to support backtesting and bot development. Currently, we only support Binance exchange. If you want to include support for other exchanges, you need to implement a new struct... -
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LangChain
⚡ Building applications with LLMs through composability ⚡
Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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Olares
Olares: An Open-Source Sovereign Cloud OS for Local AI
Olares is an AI-powered chatbot framework designed to support real-time natural language understanding and response generation. -
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cuML
RAPIDS Machine Learning Library
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU... -
JobNimbus Construction SoftwareTrack leads, jobs, and tasks from one easy to use software. You can access your information wherever you are, get everyone on the same page, and grow your business.
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Best-of Machine Learning with Python
A ranked list of awesome machine learning Python libraries
This curated list contains 900 awesome open-source projects with a total of 3.3M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! General-purpose machine learning and deep learning... -
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AWS Neuron
Powering Amazon custom machine learning chips
... continue to use the same ML frameworks you use today and migrate your software onto Inf1 instances with minimal code changes and without tie-in to vendor-specific solutions. Neuron is pre-integrated into popular machine learning frameworks like TensorFlow, MXNet and Pytorch to provide a seamless training-to-inference workflow. It includes a compiler, runtime driver, as well as debug and profiling utilities with a TensorBoard plugin for visualization. -
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libvips
A fast image processing library with low memory needs
libvips is a demand-driven, horizontally threaded image processing library. Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. It has around 300 operations covering arithmetic, histograms, convolution, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric types, from 8-bit int to 128-bit complex. Images can have any number of bands. It supports a good... -
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MMOCR
OpenMMLab Text Detection, Recognition and Understanding Toolbox
... design of MMOCR enables users to define their own optimizers, data preprocessors, and model components such as backbones, necks and heads as well as losses. Please refer to Getting Started for how to construct a customized model. The toolbox provides a comprehensive set of utilities which can help users assess the performance of models. It includes visualizers which allow visualization of images, ground truths as well as predicted bounding boxes, and a validation tool for evaluating checkpoints. -
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ShaHaN SSH Panel
SSH User Management With Add/Delete Users
SSH user management with add/delete users, online users, and limit users. -
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MindNLP
Easy-to-use and high-performance NLP and LLM framework
MindNLP is a natural language processing library built on the MindSpore framework, providing tools and models for various NLP tasks. -
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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. -
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pmdarima
Statistical library designed to fill the void in Python's time series
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function. -
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Telegram for GitHub Actions
GitHub Action that sends a Telegram message.
GitHub Action for sending a Telegram notification message. -
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BetaML.jl
Beta Machine Learning Toolkit
The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, Python, R and any other language with a Julia binding. All models are implemented entirely in Julia and are hosted in the repository itself (i.e. they are not wrapper to third-party models). If your favorite option or model is missing, you can try to implement it yourself and open a pull request to share it (see the section Contribute below) or request its... -
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Recommenders
Best practices on recommendation systems
The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several state... -
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AIaC
Artificial Intelligence Infrastructure-as-Code Generator
aiac is a command line tool to generate IaC (Infrastructure as Code) templates, configurations, utilities, queries and more via OpenAI's API. The CLI allows you to ask the model to generate templates for different scenarios (e.g. "get terraform for AWS EC2"). It will make the request, and store the resulting code to a file, or simply print it to standard output. By default, aiac uses the same model used by ChatGPT, but allows using different models. -
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canvas-constructor
An ES6 utility for canvas with built-in functions and chained methods
An ES6 utility for canvas with built-in functions and chained methods. Alternatively, you can import canvas-constructor/browser. That will create a canvas with size of 300 pixels width, 300 pixels height. Set the color to #AEFD54. Draw a rectangle with the previous color, covering all the pixels from (5, 5) to (290 + 5, 290 + 5) Set the color to #FFAE23. Set the font size to 28 pixels with font Impact. Write the text 'Hello World!' in the position (130, 150) Return a buffer. -
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Sonnet
TensorFlow-based neural network library
Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already... -
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Kalavai
Turn everyday devices into your own AI cluster
Kalavai is a self-hosted platform that turns everyday devices into your very own AI cluster. Do you have an old desktop or a gaming laptop gathering dust? Aggregate resources from multiple machines and say goodbye to CUDA out-of-memory errors. Deploy your favorite open-source LLM, fine-tune it with your own data, or simply run your distributed work, zero-DevOps. Simple. Private. Yours. -
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Spektral
Graph Neural Networks with Keras and Tensorflow 2
... deep learning. Spektral also includes lots of utilities for representing, manipulating, and transforming graphs in your graph deep learning projects. Spektral is compatible with Python 3.6 and above, and is tested on the latest versions of Ubuntu, MacOS, and Windows. Other Linux distros should work as well. The 1.0 release of Spektral is an important milestone for the library and brings many new features and improvements.