Official DeiT repository. Contribute to facebookresearch/deit development by creating an account on GitHub.

Dec 23, 2020 · Recently, neural networks purely based on attention were shown to address image understanding tasks such as image classification. However, these visual transformers are pre-trained …

Dec 23, 2020 · Data-efficient image Transformers (DeiT) use less data and computing resources to produce high-performance image classification AI models, and help the broader academic …

Aimv2 BEiT BiT Conditional DETR ConvNeXT ConvNeXTV2 CvT D-FINE DAB-DETR Deformable DETR DeiT Depth Anything Depth Anything V2 DepthPro DETA DETR DiNAT DINOV2 DINOv2 with …

Feb 11, 2022 · DeiT has the same architecture as ViT except the input token part that having an additional distillation token. But since ViT cannot perform well when trained on insufficient amounts …

Jul 10, 2023 · DeiT (Data-efficient image Transformers) expands on this approach by introducing a distillation token [DLS] at the end of the input sequence. The embedding of this token is utilized to …

Data-efficient Image Transformer (DeiT) model pre-trained and fine-tuned on ImageNet-1k (1 million images, 1,000 classes) at resolution 224x224. It was first introduced in the paper Training data …

Oct 17, 2024 · DeiT is a new VIT method to handle the problem of VIT requiring a large amount of data. It incorporates a distillation token and learns from the teacher model's prediction to imitate the ability …

Jul 12, 2024 · DeiT (Data-efficient Image Transformer) is an advanced vision transformer model designed to achieve high performance in image classification tasks with significantly less data …

Today we are going to implement Training data-efficient image transformers & distillation through attention a new method to perform knowledge distillation on Vision Transformers called DeiT.