# Transformer encoder

A vision Transformer model trained using the DINOv2 method for self-supervised image feature extraction

Vision Transformer model trained using the DINOv2 method, extracting image features through self-supervised learning

This Vision Transformer (ViT) model is pre-trained on the ImageNet-21k dataset and then fine-tuned on the ImageNet dataset, suitable for image classification tasks.

A Vision Transformer model pretrained on ImageNet-21k, featuring an extra-large architecture suitable for visual tasks like image classification.

A Russian RoBERTa large model pre-trained by SberDevices team with 355 million parameters, trained on 250GB of Russian text

This Vision Transformer (ViT) model is pre-trained on the ImageNet-21k dataset and is suitable for image classification tasks.

Vision Transformer (ViT) is an image classification model based on the transformer architecture, pre-trained on ImageNet-21k and fine-tuned on ImageNet.

A Vision Transformer model pretrained on the ImageNet-21k dataset, suitable for image feature extraction and downstream task fine-tuning.