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A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases…
A clean, modular implementation of the Yolov7 model family, which uses the official pretrained weights, with utilities for training the model on custom (non-COCO) tasks.
A lightweight and convenient tool which can be used to turn a Python function into a command line script, with minimal boilerplate! A thin wrapper around argparse, with are no additional dependencies!
A clean, modular implementation of the Proximal Policy Optimization (PPO) algorithm in PyTorch, written with a strong focus on readability and educational value, as well as performance.