This is a collection of our NAS and Vision Transformer work.
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 project provides the source code for the vision longformer paper.
This repository contains PyTorch code for ConViT. It builds on code from the Data-Efficient Vision Transformer and from timm.
Las características principales de facebookresearch/convit son: Efficient Vision Architectures, Efficient Vision Transformers, Vision Transformers.
Las alternativas de código abierto para facebookresearch/convit incluyen: microsoft/cream — This is a collection of our NAS and Vision Transformer work. ofsoundof/localvit — This repository contains the PyTorch training and evaluation code for LocalViT. facebookresearch/deit — DeiT is a PyTorch vision transformer framework designed for image classification. It implements a transformer-based… ibm/crossvit — Official implementation of CrossViT. https://arxiv.org/abs/2103.14899. microsoft/vision-longformer — This project provides the source code for the vision longformer paper. raoyongming/dynamicvit — This repository contains PyTorch implementation for DynamicViT (NeurIPS 2021).
