A Python library for secure and private Deep Learning built on PyTorch and TensorFlow.
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PyTorch is a Python package providing tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. It includes components such as torch, torch.autograd, torch.nn, and torch.utils, and can be used as a NumPy replacement or a deep learning research platform.
Radiata is a stable diffusion web UI built on the diffusers library that uses TensorRT high-speed inference technology. Its official documentation provides resources for introduction, installation, usage, developer guidance, and troubleshooting for Windows and Linux operating systems. It is categorized under AI & Machine Learning with a focus on AI image generation.
REAL Video Enhancer is a GUI application for frame interpolation, upscaling, decompression and denoising of videos on Linux, Windows and macOS. It offers RIFE and GMFSS interpolation models and several upscale models, with TensorRT, PyTorch and NCNN backends. It includes scene change detection and a preview of the latest rendered frame.
Open-source runtime for numerical computing that executes MATLAB-syntax code. Built in Rust, it provides a compiler, a virtual machine, and JIT tiers, with a GPU backend powered by wgpu. The project targets CPU and GPU hardware and handles tensor allocations and movement automatically.
SciRuby is a project providing tools for scientific computing and data visualization in Ruby. Its releases include NMatrix, a linear algebra library with dense and sparse matrix storage and tensor support, alongside visualization and statistics gems. The project describes itself as currently alpha, and it notes its gems are tested but not battle-hardened. SciRuby and NMatrix are available under the BSD three-clause license.
segmentation models is a software library that provides image segmentation models with pretrained backbones, designed for use with Keras and TensorFlow Keras frameworks. It is available as a public open source repository on GitHub.
A Hugging Face Space that accepts uploaded or recorded audio and returns a text transcription with grammar correction. The page reports a runtime error because none of PyTorch, TensorFlow >= 2.0, or Flax were found, so models are unavailable.
Talos is a Python package for running parameter sweeps for Keras, TensorFlow and PyTorch models. Experiments can use the Python Scan interface or a single-file definition run through Python or the CLI. The Talos 2 generation is in active maintenance, and the Talos 1.x series will remain supported at least until 2028.
TensorFlow's Visualization Toolkit.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
TensorForce is an open-source library built on TensorFlow for applied reinforcement learning. Hosted on GitHub, the project provides installation guidance, quickstart example code, and command line usage documentation for users.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
tensorlm is an open-source wrapper library for text generation and language model use cases. It supports character and word level recurrent neural network (RNN) implementations built on TensorFlow, and includes installation guidance, basic and advanced usage documentation, and command line usage instructions.
tensorpack is an open-source neural network training interface built on TensorFlow with a focus on training speed and flexibility. Hosted on GitHub, the project provides feature documentation and example materials covering use cases including computer vision, reinforcement learning, and speech or natural language processing.
TextGen is an open-source desktop app for local LLMs, with text, vision, tool-calling and web search, plus a UI and API. It supports multiple backends including llama.cpp, Transformers, ExLlamaV3 and TensorRT-LLM, and an OpenAI/Anthropic-compatible API. It also offers LoRA training and image generation. Portable builds are provided for Linux, Windows and macOS.
TF-GAN is a lightweight library for training and evaluating Generative Adversarial Networks in TensorFlow. It provides core training infrastructure, common GAN operations and normalization techniques, losses and penalties such as the Wasserstein loss and gradient penalty, and standard evaluation metrics including Inception Score, Frechet Distance and Kernel Distance. It can be installed with pip. The repository was archived and is now read-only.
Tribuo is a machine learning library written in Java, developed by Oracle Labs' Machine Learning Research Group and released under the Apache 2.0 license. It supports classification, regression, clustering, anomaly detection and multi-label classification, and provides interfaces to libraries such as XGBoost and TensorFlow along with ONNX model exchange support.
Tune is a Python library for experiment execution and hyperparameter tuning at any scale. It supports machine learning frameworks including PyTorch, XGBoost, and TensorFlow and Keras, and runs algorithms such as Population Based Training (PBT) and HyperBand/ASHA. It also integrates with hyperparameter optimization tools including Ax, BayesOpt, BOHB, Nevergrad, and Optuna.
Vega is an AutoML algorithm tool chain developed by Noah's Ark Laboratory. It covers hyperparameter optimization, data augmentation, network architecture search, model compression and fully train functions, and supports PyTorch, TensorFlow and MindSpore backends.
Vespa is an AI search platform. Its repository contains the code required to build and run Vespa. The project covers searching, making inferences in and organizing vectors, tensors, text and structured data at serving time and any scale. It is licensed under Apache 2.0.
A public archive of acceleration techniques for the Stable Diffusion model intended to help generate images faster and more efficiently. It covers AITemplate, nvFuser, TensorRT and FlashAttention, with example images and benchmarks. The repository was archived by the owner on Oct 24, 2025, and is now read-only.
Zetane Viewer is a free tool for visualizing machine learning and artificial neural network models, including architecture and internal data such as feature maps, weights, biases and layer output tensors. The viewer supports .ONNX and .ZTN files and is available for Windows, Linux and Mac. It can also be launched from existing scripts or notebooks via the Zetane Python API.