Vision Transformer

Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224. It was introduced in the paper An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. The weights were converted from the ViT-L_16.npz file in GCS buckets presented in the original repository.

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Safetensors

Model size

327M params

Tensor type

F32

Inference Providers NEW

Image Feature Extraction

This model is not currently available via any of the supported third-party Inference Providers, and the HF Inference API does not support transformers models with pipeline type image-feature-extraction