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 …

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 …

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 …

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 …

Introduced to address the challenge of achieving strong performance with limited labeled data, DeiT leverages distillation techniques and large-scale unlabeled datasets during training.

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 …

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.

DeiT (data-efficient image transformers) are more efficiently trained transformers for image classification, requiring far less data and far less computing resources compared to the original …

Hands-on tutorial for DeiT In this notebook, we show how to use the pre-trained models that we provide with torchhub to perform predictions