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README.md

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 ### Model and Inputs
-Prithvi is a first-of-its-kind temporal Vision Transformer (ViT) model pre-trained by the IBM and NASA team on contiguous US Harmonised Landsat and Sentinel 2 (HLS) data. The model adopts a self-supervised encoder developed with a ViT architecture and Masked Autoencoder (MAE) learning strategy, with an L1 loss function. The model includes spatial attention across multiple patches and temporal attention for each patch. 
+Prithvi is a first-of-its-kind temporal Vision transformer pre-trained by the IBM and NASA team on contiguous US Harmonised Landsat Sentinel 2 (HLS) data. Particularly, the model adopts a self-supervised encoder developed with a ViT architecture and Masked AutoEncoder learning strategy with an MSE loss function. The model includes spatial attention across multiple patches and also temporal attention for each patch. 
 
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