A ROS-Industrial meta-package that provides the necessary configurations and descriptions to control and simulate Universal Robots hardware using ROS.

A collection of text processing classes and ops for TensorFlow that enables consistent preprocessing in the TensorFlow graph for both training and inference.

A Python module for survival analysis built on scikit-learn that allows researchers to connect covariates to event times while handling censored data.

A local-first long-term memory runtime for macOS that creates an evidence-linked personal model of a user's work patterns and goals to provide grounded context for AI coding agents via MCP.

A memory-optimized Batch Normalization layer for PyTorch that reduces GPU memory usage by up to 50% during training by combining BN and activation into an in-place operation.

An open-source browser automation agent that runs inside your existing browser, allowing AI agents to control your live sessions via natural language or MCP.

YiGraph is an intelligent graph data analysis agent system that uses the AAG framework to convert natural language questions into executable graph algorithm workflows for complex relational data analysis.

A lightweight Rust-based proxy that turns Claude.ai and Claude Code into OpenAI-compatible API endpoints using session cookies.

A tool for computing shareable, comparable, and reproducible BLEU and other translation metrics, automating test set management and tokenization.

A scalable dataloading library for PyTorch that introduces stateful loading for mid-epoch checkpointing and composable iterators for data preprocessing.

A PyTorch-based library that brings Hugging Face Transformer architectures to sequential and session-based recommendation systems, supporting rich tabular input features and GPU acceleration.

An open protocol and framework that standardizes how AI agents perceive the real world by providing structured, real-time data via a system of interchangeable sensors.

A Python library for converting biomolecular structures and interaction networks into geometric graph representations for use in deep learning.

A high-performance C++ library for implementing neural networks used in advanced analytics for business, healthcare, and engineering.

A Haskell library for tensors and neural networks that leverages the core C++ libraries shared by PyTorch.

A collection of Python scripts for converting object detection dataset annotations between CSV, COCO, Pascal VOC, and Labelme formats.

Uni-MoE is a Mixture-of-Experts based omnimodal large model capable of understanding and generating across multiple modalities, including text, images, and speech.

An open-source agentic framework for building research agents using Schema-Guided Reasoning to combine structured reasoning with flexible tool selection.

An offline OCR library for Android that enables high-speed recognition of Chinese ID cards, driver's licenses, and passports without requiring an internet connection.

The core speech synthesis engine for VOICEVOX, provided as a C and Python library for easy integration into various applications.

A JAX library for building and sampling probabilistic graphical models, focusing on efficient block Gibbs sampling and energy-based models.

A PyTorch quantization backend for Optimum that reduces model size and memory usage by converting weights and activations to lower precision like int4 or float8.

A Rust crate that wraps the Ollama local‑model HTTP API, providing easy functions for text generation, chat (with history), streaming responses, model management, embeddings, and LLM‑tool/function calling via a macro‑based system.

A GPU-accelerated recommender framework designed for the efficient training and inference of large deep learning models with massive embedding tables.

A comprehensive and unified deep reinforcement learning library providing a modularized ensemble of DRL and MARL algorithms compatible with PyTorch, TensorFlow, and MindSpore.

Apache SystemDS is an open-source machine learning system that manages the end-to-end data science lifecycle from data preparation to model serving using a high-level language.

A high-performance library for small dense and sparse linear algebra operations that uses JIT code generation to optimize deep learning and HPC workloads across multiple CPU architectures.

A packaged version of the Segment Anything Model (SAM) that provides easy pip installation and extended support for video segmentation and cloud GPU integration.

A library for point cloud registration using probabilistic models, offering a more robust alternative to ICP for both rigid and non-rigid transformations.

A Sharded Data Parallelism framework by Yandex that optimizes LLM pre-training by reducing communication and memory overhead, offering up to 20% speedup over PyTorch FSDP.

EnsoAI is an Electron‑based desktop workbench that couples Git worktree management with persistent AI‑agent sessions (Claude, Gemini, Codex, etc.). It provides a built‑in Monaco editor, visual Git UI, 3‑way merge tool, and one‑click IDE bridging, enabling developers to work on multiple branches in parallel while each branch enjoys its own dedicated LLM context.

A TensorFlow framework for training neural networks using structured signals, such as graphs and adversarial perturbations, to improve accuracy with limited labeled data and increase robustness.

A Triton Inference Server backend that enables high-performance serving of TensorRT-LLM optimized models with support for in-flight batching and multi-GPU scaling.

MushroomRL is a modular Python library for reinforcement learning that provides a wide array of classical and deep RL algorithms and integrates with popular tensor libraries and benchmarks.

A ROS-based full-stack software framework for agile quadrupedal locomotion that integrates planning, control, and estimation for simulation and hardware.

A modern Java library for genetic and evolutionary algorithms that provides tools for optimization, genetic programming, and multi-objective search.

A PyGlove-powered library that enables object-oriented prompting, allowing developers to integrate natural language and structured Python objects for more predictable LLM outputs.

A comprehensive deep learning utility library and CLI tool providing visualization, annotation management, and deployment utilities for computer vision and 3D data.

A machine learning library for Ruby that provides a wide array of algorithms with an interface similar to Scikit-Learn.

A Julia package that integrates differential equation solvers into neural networks to enable the creation of physically informed scientific machine learning models.

A collection of hardware-aware efficient ConvNet models and tools, including FBNet and ChamNet, designed to optimize computer vision performance and latency on mobile devices.

TensorFlow‑Java provides Maven‑publishable Java/JVM bindings for TensorFlow, including low‑level JNI wrappers (`tensorflow‑core`), a high‑level neural‑network API (`tensorflow‑framework`), and an independent ndarray library. It supports Linux (x86_64, arm64) and macOS (Apple Silicon) binaries, with optional GPU builds, and integrates with standard Java build tools.

A comprehensive benchmark and framework for stereo matching that integrates 17 datasets and multiple state-of-the-art models for depth estimation.

A deep learning toolbox for predicting quantum-chemical properties of molecules and materials using atomistic neural networks.

hf‑mem is a lightweight Python CLI (and library) that estimates the RAM required to run any Hugging Face model that uses Safetensors or GGUF weights. It fetches only metadata via HTTP range requests, supports Transformers, Diffusers, Sentence‑Transformers, and can optionally estimate KV‑cache memory and MoE breakdowns. Installable as a standalone tool, a Hugging Face CLI extension, or an agent skill.

An AI-powered offensive security agent that automates privilege escalation to root access using an autonomous LLM-driven shell loop.

DiffMem is a production‑ready FastAPI service that gives LLM‑powered agents a Git‑backed, Markdown‑based memory. Each user lives on an isolated Git branch; the writer agent commits conversation updates, and a retrieval agent uses plain `git`/`grep` commands to fetch the current view or dive into history. The system needs only an LLM API key, runs on a tiny Linux box (Docker or Coolify), and optionally mirrors branches to a private GitHub repo for backup. It includes consolidation tools (dedupe, redistribute, link) to keep the “now” files compact and well‑linked.

An R interface to Keras that enables R users to prototype and train deep learning models using a high-level neural networks API.