This is a collection of our NAS and Vision Transformer work.
Die Hauptfunktionen von microsoft/cream sind: Efficient Vision Architectures, Efficient Vision Transformers, Hybrid Vision Architectures, Vision Backbones and Classification, Vision Transformers, Model Compression.
Open-Source-Alternativen zu microsoft/cream sind unter anderem: ibm/crossvit — Official implementation of CrossViT. https://arxiv.org/abs/2103.14899. raoyongming/dynamicvit — This repository contains PyTorch implementation for DynamicViT (NeurIPS 2021). facebookresearch/deit — DeiT is a PyTorch vision transformer framework designed for image classification. It implements a transformer-based… facebookresearch/levit — LeViT a Vision Transformer in ConvNet's Clothing for Faster Inference. facebookresearch/convit — This repository contains PyTorch code for ConViT. It builds on code from the Data-Efficient Vision Transformer and… danczs/visformer — This is a pytorch implementation for the Visformer models. This project is based on the training code in DeiT and the…
This repository contains PyTorch implementation for DynamicViT (NeurIPS 2021).
DeiT is a PyTorch vision transformer framework designed for image classification. It implements a transformer-based architecture that processes images as sequences of flattened patches using self-attention layers and position-aware sequence modeling instead of convolutional filters. The project focuses on data-efficient training through a knowledge distillation framework. This system allows a student model to mimic the soft labels of a high-performance teacher model to improve accuracy and generalization, particularly when training on smaller datasets. The library covers the full development
This is a pytorch implementation for the Visformer models. This project is based on the training code in DeiT and the tools in timm.