The Best FastDatasets Alternatives in 2026

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

LLMeBench provides a flexible framework for benchmarking large language models.

An open-source visual programming environment for battle-testing prompts to LLMs.

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

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

Snorkel helps generate training data programmatically through weak supervision.

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

The Hugging Face Open LLM Leaderboard compares language models across evaluation tests including IFEval, MATH, and MMLU-Pro.

SpeechMap.AI compares language models’ refusal rates on controversial speech topics.

OpenLM Arena compares open language models through leaderboards and benchmark results.

This NBER paper studies language models as both researchers and subjects in automated social science.

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

VoxelBench benchmarks language models on creating voxel builds from prompts.

Apache Spark is a unified engine for large-scale data processing and analytics.

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

AutoViz automatically creates visualizations for datasets of different sizes from a single line of code.

NALP covers Natural Adversarial Language Processing through a dedicated library.

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

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

PyTorch Frame provides a library for applying deep learning models to tabular data.

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

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.

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