Popular GitHub Repositories for Pytorch Lightning

SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild. Our new online demo is also released at suppixel.ai.

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ???

Time series forecasting with PyTorch

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023

NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning

? Monitor deep learning model training and hardware usage from your mobile phone ?

Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7 data domains

A standard framework for modelling Deep Learning Models for tabular data

A template for deep learning projects, designed for PyTorch and PyTorch Lightning users

Instant-ngp in pytorch+cuda trained with pytorch-lightning (high quality with high speed, with only few lines of legible code)

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery, ISPRS. Also, including other vision transformers and CNNs for satellite, aerial image and UAV image segmentation.

Deep learning with spiking neural networks (SNNs) in PyTorch.

Blazing fast framework for fine-tuning similarity learning models

Unofficial PyTorch Implementation for FaceShifter (https://arxiv.org/abs/1912.13457)

End-To-End Molecular Dynamics (MD) Engine using PyTorch

Flexible components pairing ? Transformers with :zap: Pytorch Lightning

? 首个CJK（中日韩）字体识别以及样式提取模型 YuzuMarker的字体识别模型与实现 / First-ever CJK (Chinese Japanese Korean) Font Recognition and Style Extractor, side project of YuzuMarker

A PyTorch implementation of Perceiver, Perceiver IO and Perceiver AR with PyTorch Lightning scripts for distributed training

minLoRA: a minimal PyTorch library that allows you to apply LoRA to any PyTorch model.

Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.