Simple but robust implementation of LoRA for PyTorch. Compatible with NLP, CV, and other model types. Strongly typed and tested.

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

The official implementation of [CVPR2022] Decoupled Knowledge Distillation https://arxiv.org/abs/2203.08679 and [ICCV2023] DOT: A Distillation-Oriented Trainer https://openaccess.thecvf.com/content…

Code for the paper: Rotating Features for Object Discovery

Code for the paper: Complex-Valued Autoencoders for Object Discovery

GEKKO Python for Machine Learning and Dynamic Optimization

AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.

3D Reconstruction Software

Official Implementation of CVPR 2023 paper: "VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution"

A Harder ImageNet Test Set (CVPR 2021)

Code for our CVPR 2022 workshop paper "Towards Exemplar-Free Continual Learning in Vision Transformers"

Fine-tuning Vision Transformers on various classification datasets

An easy-to-use implementation of Barlow Twins for Pytorch.

This is the official GitHub for paper: On the Versatile Uses of Partial Distance Correlation in Deep Learning, in ECCV 2022

A non-official 100% PyTorch implementation of META-DATASET benchmark for few-shot classification

[Spotlight ICLR 2023 paper] Continual evaluation for lifelong learning with neural networks, identifying the stability gap.

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

Self-supervised vision transformers for joint SAR-optical representation learning

Awesome Incremental Learning

A clean and simple data loading library for Continual Learning

Avalanche: an End-to-End Library for Continual Learning based on PyTorch.

Vision Transformers with Hierarchical Attention

A UE4 set of tools to deform meshes at runtime.

Open-source simulator for autonomous driving research.

Deep learning with cats (^._.^)

PyTorch implementation of YOLO-v1 including training

A JIT Compiler for Neural Network Inference

Share numpy arrays across processes efficiently ideal for large, read-only datasets