lxqt-powermanagement is providing tools to monitor power management events and optionally trigger actions like e. g. shut down a system when laptop batteries are low on power.

This package contains a CLI MIME tool, qtxdg-mat, for handling file associations and opening files with their default applications.

Lxqt-build-tools is providing several tools needed to build LXQt itself as well as other components maintained by the LXQt project.

This package provides a Qt graphical interface to archiving programs like tar and zip.

libstatgrab is a library that provides cross platform access to statistics about the system on which it's run.

LXImage-Qt is the Qt port of LXImage, a simple and fast image viewer.

lxqt-qtplugin is providing a library libqtlxqt to integrate Qt with LXQt.

GNU M4 is an implementation of the M4 macro language, which features some extensions over other implementations, some of which are required by GNU Autoconf. It is used as a macro processor, which means it processes text, expanding macros as it encounters them. It also has some built-in functions, for example to run shell commands or to do arithmetic.

Thread-pool Controls provides Python helpers to limit the number of threads used in the threadpool-backed of common native libraries used for scientific computing and data science (e.g. BLAS and OpenMP).

cleanlab automatically finds and fixes errors in any ML dataset. This data-centric AI package facilitates machine learning with messy, real-world data by providing clean labels during training.

Vowpal Wabbit is a machine learning system with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

Lap is a linear assignment problem solver using Jonker-Volgenant algorithm for dense (LAPJV) or sparse (LAPMOD) matrices.

PyG is a library built upon PyTorch to easily write and train Graph Neural Networks for a wide range of applications related to structured data.

This package provides a reimplementation of OpenAI's Whisper model using CTranslate2, which is a inference engine for transformer models.

XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way.

ONNX Interface for Framework Integration is a cross-platform API for loading and executing ONNX graphs on optimized backends. This package contains facebook extensions and is used by PyTorch.

Brian is a simulator for spiking neural networks written in Python. It is therefore designed to be easy to learn and use, highly flexible and easily extensible.

PyTorch Lightning is just organized PyTorch; Lightning disentangles PyTorch code to decouple the science from the engineering.

Captum is a model interpretability and understanding library for PyTorch. Captum contains general purpose implementations of integrated gradients, saliency maps, smoothgrad, vargrad and others for PyTorch models. It has quick integration for models built with domain-specific libraries such as torchvision, torchtext, and others.

This library is used internally as header-only library by PyTorch.

CTranslate2 is a C++ and Python library for efficient inference with Transformer models.

The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU.

The GeomLoss library provides efficient GPU implementations for:

• Kernel norms (also known as Maximum Mean Discrepancies).

• Hausdorff divergences, which are positive definite generalizations of the Chamfer-ICP loss and are analogous to log-likelihoods of Gaussian Mixture Models.

• Debiased Sinkhorn divergences, which are affordable yet positive and definite approximations of Optimal Transport (Wasserstein) distances.

OpenFst is a library for constructing, combining, optimizing, and searching weighted finite-state transducers (FSTs).

This package provides simple access speech to text for using in Linux without being tied to a desktop environment, using the vosk-api. The user configuration lets you manipulate text using Python string operations. It has zero overhead, as this relies on manual activation and there are no background processes. Dictation is accessed manually with nerd-dictation begin and nerd-dictation end commands.