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README.md

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 ### Model and Inputs
-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. The model adopts a self-supervised encoder developed with a ViT architecture and Masked AutoEncoder (MAE) learning strategy, with an MSE loss function. The model includes spatial attention across multiple patches and also temporal attention for each patch.
+Prithvi-EO-1.0 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. The model adopts a self-supervised encoder developed with a ViT architecture and Masked AutoEncoder (MAE) 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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