Add V2 link

README.md

@@ -1,6 +1,6 @@
 ---
 title: Prithvi 100M Demo
-emoji: 🏆
+emoji: 🌎
 colorFrom: gray
 colorTo: blue
 sdk: docker

app.py

@@ -377,6 +377,8 @@ with gr.Blocks() as demo:
     gr.Markdown(value='''Prithvi is a first-of-its-kind temporal Vision transformer pretrained by the IBM and NASA team on continental 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 a MSE as a loss function. The model includes spatial attention across multiple patchies and also temporal attention for each patch. More info about the model and its weights are available [here](https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M).\n
 This demo showcases the image reconstracting over three timestamps, with the user providing a set of three HLS images and the model randomly masking out some proportion of the images and then reconstructing them based on the not masked portion of the images.\n
 The user needs to provide three HLS geotiff images, including the following channels in reflectance units: Blue, Green, Red, Narrow NIR, SWIR, SWIR 2.
+
+Check out our newest model: [Prithvi-EO-2.0-Demo](https://huggingface.co/spaces/ibm-nasa-geospatial/Prithvi-EO-2.0-Demo).
 ''')
     with gr.Row():
         with gr.Column():