The Best PyTorch Frame Alternatives in 2026

pytorch tabular provides a unified framework for deep learning models on tabular data.

This TabGAN repository reviews research on applying GANs to generate tabular data.

Captum explains model behavior and supports interpretability analysis for PyTorch systems.

Disco’s discovery engine finds statistically validated patterns in tabular data, including feature interactions and subgroup effects.

A Python package to assess and improve fairness of machine learning models.

This repository implements YOLOv3 variants in PyTorch for real time object detection, training, validation, inference, and export.

PyTorch Geometric provides graph neural network tools and libraries for PyTorch projects.

GPyTorch provides an efficient implementation of Gaussian processes using PyTorch.

Ultralytics YOLOv5 supports object detection, instance segmentation, classification, training, and export in PyTorch.

An open source Python library for drift detection in machine learning systems.

The lightly Python library supports self supervised learning on images.

nilearn provides Python tools for machine learning and neuroimaging analysis.

Feature Engine provides Python tools for feature engineering and selection that are compatible with scikit-learn.

Python package which helps to debug machine learning classifiers and explain their predictions.

modAL provides a modular active learning framework for Python built on top of scikit-learn.

Automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.

WhichLLM tests local language models on a user’s hardware and ranks them using recent benchmarks.

FastDatasets helps create training datasets for large language models.

AIF360 provides fairness metrics and explanations for datasets and models, along with algorithms to mitigate bias.

This repository provides segmentation models with pretrained backbones for Keras and TensorFlow Keras.

This repository provides semantic segmentation models with more than 500 pretrained convolutional and transformer backbones.

Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.

Ultralytics supports detection, segmentation, image classification, pose estimation, and tracking across YOLO model versions.

Adala automates data labeling through an autonomous agent framework for organizing labeled datasets.