# Vision Transformer architecture

Sapiens is a family of Vision Transformer models pre-trained on 300 million 1024x1024 resolution human images, focusing on human-centric vision tasks.

Sapiens is a family of Vision Transformer models pre-trained on 300 million 1024×1024 resolution human images, focusing on human-centric vision tasks.

This Vision Transformer (ViT) model is pretrained on the ImageNet-21k dataset at 224x224 resolution, suitable for image classification tasks.

This is a Dense Prediction Transformer (DPT) model fine-tuned on the ADE20k dataset for semantic segmentation tasks.

A monocular depth estimation model based on Vision Transformer (ViT), trained on 1.4 million images, suitable for zero-shot depth prediction tasks.

BEiT is an image segmentation model based on Vision Transformer architecture, achieving efficient semantic segmentation through self-supervised pre-training and fine-tuning on the ADE20k dataset.