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Verified signatureModel Overview: The Vision Transformer (ViT) is a transformer encoder model designed for image recognition tasks. It was pretrained on a large dataset of 14 million images and 21,843 classes known as ImageNet-21k, and fine-tuned on ImageNet 2012, which consists of 1 million images across 1,000 classes. How It Works: Input Representation: Images are split into fixed-size patches (16x16 pixels) and linearly embedded. A special [CLS] token is added at the beginning of the sequence to indicate the image's classification. Transformer Encoder: The model uses a transformer encoder architecture, similar to BERT for text, to process the image patches. Absolute position embeddings are added to encode spatial information before inputting the sequence into transformer layers. Classification: After processing through the transformer layers, the output from the [CLS] token is used for image classification. This token's final hidden state represents the entire image's features. Intended Uses: I…1d4177d -
Update README.md
Verified signatureModel Overview: The Vision Transformer (ViT) is a transformer encoder model designed for image recognition tasks. It was pretrained on a large dataset of 14 million images and 21,843 classes known as ImageNet-21k, and fine-tuned on ImageNet 2012, which consists of 1 million images across 1,000 classes. How It Works: Input Representation: Images are split into fixed-size patches (16x16 pixels) and linearly embedded. A special [CLS] token is added at the beginning of the sequence to indicate the image's classification. Transformer Encoder: The model uses a transformer encoder architecture, similar to BERT for text, to process the image patches. Absolute position embeddings are added to encode spatial information before inputting the sequence into transformer layers. Classification: After processing through the transformer layers, the output from the [CLS] token is used for image classification. This token's final hidden state represents the entire image's features. Intended Uses: I…cfbfb4b -
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