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  ### Model and Inputs
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- 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 L1 loss function. The model includes spatial attention across multiple patches and also temporal attention for each patch.
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  ![](GFM.png)
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  ### Model and Inputs
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+ 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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  ![](GFM.png)
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