This is a package for hassle-free computation of shareable, comparable, and reproducible BLEU, chrF, and TER scores for natural language processing.

TorchMetrics is a collection of 100+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. It offers:

• A standardized interface to increase reproducibility

• Reduces boilerplate

• Automatic accumulation over batches

• Metrics optimized for distributed-training

• Automatic synchronization between multiple devices

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.

DMLC-Core is the backbone library to support all DMLC projects, offers the bricks to build efficient and scalable distributed machine learning libraries.

LinearOperator is a PyTorch package for abstracting away the linear algebra routines needed for structured matrices (or operators).

jaxtyping provides type annotations and runtime checking for shape and dtype of JAX arrays, PyTorch, NumPy, TensorFlow, and PyTrees.

PyTorch is a Python package that provides two high-level features:

• tensor computation (like NumPy) with strong GPU acceleration;

• deep neural networks (DNNs) built on a tape-based autograd system.

You can reuse Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed.

Note: currently this package does not provide GPU support.

Gloo is a collective communications library. It comes with a number of collective algorithms useful for machine learning applications. These include a barrier, broadcast, and allreduce.

Hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models.

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

TensorFlow is a flexible platform for building and training machine learning models. This package provides the "lite" variant for mobile devices.

Kaldi is an extensible toolkit for speech recognition written in C++.

OpenMM is a toolkit for molecular simulation. It can be used either as a stand-alone application for running simulations, or as a library you call from your own code.

Pomegranate is a graphical models library for Python, implemented in Cython for speed.

LibreTranslate is a machine translation API and web interface, powered by the Argos Translate library.

Apache Burr makes it easy to develop applications that make decisions (chatbots, agents, simulations, etc...) from simple Python building blocks. Apache Burr works well for any application that uses LLMs, and can integrate with any of your favorite frameworks. Burr includes a UI that can track/monitor/trace your system in real time, along with pluggable persisters (e.g. for memory) to save and load application state.

This package provides a Plain C/C++ implementation based on ggml, working in the same way as llama.cpp. It supports diffusion models such as SD, Flux, Wan, Qwen and Image,Z-Image.

The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision.

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.

Gloo is a collective communications library. It comes with a number of collective algorithms useful for machine learning applications. These include a barrier, broadcast, and allreduce.

Visualization and NeuroML import/export tools for the Brian 2 simulator.

apricot implements submodular optimization for the purpose of summarizing massive data sets into minimally redundant subsets that are still representative of the original data. These subsets are useful for both visualizing the modalities in the data and for training accurate machine learning models with just a fraction of the examples and compute.

GPy is a Gaussian Process (GP) framework written in Python, from the Sheffield machine learning group. GPy implements a range of machine learning algorithms based on GPs.

Argos Translate uses OpenNMT for translations and can be used as either a Python library, command-line, or GUI application. It supports installing language model packages which are ZIP archives with a .argosmodel extension. This package provides a Qt interface for Argos Translate.