Model card for vit tiny patch16 224.augreg in21k A Vision Transformer (ViT) image classification model. Trained on ImageNet 21k (with additional augmentation and regularization) in JAX by paper authors, ported to PyTorch by Ross Wightman. Model Details Model Type: Image classification / feature backbone Model Stats: Params (M): 9.7 GMACs: 1.1 Activations (M): 4.1 Image size: 224 x 224 Papers: How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers: https://arxiv.org/abs/2106.10270 An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929v2 Dataset: ImageNet 21k Original: https://github.com/google research/vision transformer Model Usage Image Classification Image Embeddings Model Comparison Explore the dataset and runtime metrics of this model in timm model results. Citation
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