Update README.md (#1)

- Update README.md (2748d479eff2304c50324dc06cf0ee46506abd82)


Co-authored-by: Johannes Schmude <johannesschmude@users.noreply.huggingface.co>

README.md

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-# Model card for granite-geospatial-downscaling
+# Model card for granite-geospatial-wxc-downscaling
 
-`granite-geospatial-downscaling` is a fine-tuned foundation model for the downscaling of weather and climate data. It is based on the [Prithvi WxC foundation model](https://huggingface.co/Prithvi-WxC). `granite-geospatial-downscaling` has been used to downscale both MERRA-2 data as well as EURO-CORDEX climate simulations. The weights for the former are included here.
+`granite-geospatial-wxc-downscaling` is a fine-tuned foundation model for the downscaling of weather and climate data. It is based on the [Prithvi WxC foundation model](https://huggingface.co/Prithvi-WxC). `granite-geospatial-downscaling` has been used to downscale both MERRA-2 data as well as EURO-CORDEX climate simulations. The weights for the former are included here.
 
 <b>6x downscaling of MERRA-2 2m temperature</b>
 
 <center><img src="downscaling_T2M_coolwarm_animated.gif" alt="Downscaling of MERRA-2 T2M" width=462></center>
 
+More information: [Code](https://github.com/IBM/granite-wxc), [base model](https://huggingface.co/Prithvi-WxC), paper (to appear).
+
 ## Architecture
 
 From an architecture point of view, we embed Prithvi WxC's transformer layers into a series of convolutional layers. That is, we typically increase resolution before and after the pre-trained transformer stages.