Models 101
UzairK/unimed-clip-vit-b16
facebook/vjepa2-vitg-fpc64-256
A frontier video understanding model developed by FAIR, Meta, which extends the pretraining objectives of VJEPA, resulting in state-of-the-a…
facebook/vjepa2-vitl-fpc64-256
A frontier video understanding model developed by FAIR, Meta, which extends the pretraining objectives of VJEPA, resulting in state-of-the-a…
MCG-NJU/videomae-base
VideoMAE model pre-trained on Kinetics-400 for 1600 epochs in a self-supervised way. It was introduced in the paper VideoMAE: Masked Autoenc…
MCG-NJU/videomae-large
VideoMAE model pre-trained on Kinetics-400 for 1600 epochs in a self-supervised way. It was introduced in the paper VideoMAE: Masked Autoenc…
timm/vit_base_patch16_224.augreg_in21k
A Vision Transformer (ViT) image classification model. Trained on ImageNet-21k (with additional augmentation and regularization) in JAX by p…
google/vit-huge-patch14-224-in21k
Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224. It was introduced in t…
google/vit-large-patch16-224-in21k
Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224. It was introduced in t…
facebook/webssl-dino1b-full2b-224
A 1 billion parameter Vision Transformer (ViT) trained with DINOv2 self-supervised learning on web-scale image data without language supervi…
facebook/webssl-dino7b-full8b-518
A 7 billion parameter Vision Transformer (ViT) trained with DINOv2 self-supervised learning on web-scale image data without language supervi…
facebook/webssl-mae1b-full2b-224
A 1 billion parameter Vision Transformer (ViT) trained with Masked Autoencoder (MAE) self-supervised learning on web-scale image data withou…