#USB

TorchSSL, a now deprecated PyTorch toolkit for semi-supervised learning (SSL), historically contributed to SSL research by implementing 11 pivotal algorithms like FlexMatch. Supporting key datasets such as CIFAR-10 and ImageNet, it offered comprehensive comparison capabilities. Despite transitioning to USB for improved efficiency, TorchSSL's configurations, logs, and model weights remain valuable for understanding SSL advancements in fields like computer vision and NLP.

Discover the USB PyTorch-based package for Semi-Supervised Learning, offering a practical framework for creating AI models in computer vision, natural language processing, and audio classification. This package includes 14 algorithms based on Consistency Regularization to optimize small datasets, making advanced AI accessible to smaller teams. The library provides essential resources, from data preparation to algorithm evaluation with comprehensive benchmarking, catering to researchers and developers aiming to improve machine learning projects.