Update README.md

README.md

@@ -32,8 +32,8 @@ The model follows the [original mae repo](https://github.com/facebookresearch/ma
 2. replace 2D positional embed with 3D positional embed;
 3. replace 2D patchify and unpatchify with 3D.
 
-### Inference
-There is an inference script (`Prithvi_run_inference.py`) that allows to run the image reconstruction on a set of three HLS images. These images have to be geotiff format, including the channels described above (Blue, Green, Red, Narrow NIR, SWIR, SWIR 2) in reflectance units.
+### Inference and demo
+There is an inference script (`Prithvi_run_inference.py`) that allows to run the image reconstruction on a set of three HLS images. These images have to be geotiff format, including the channels described above (Blue, Green, Red, Narrow NIR, SWIR, SWIR 2) in reflectance units. There is also a demo that leverages the same code [here](https://huggingface.co/spaces/ibm-nasa-geospatial/Prithvi-100M-demo)
 
 ### Finetuning examples
 Two examples of finetuning the model for image segmentation (i.e. flood detection and burn scars detection) using the mmsegmentation library are available through [github](https://github.com/NASA-IMPACT/hls-foundation-os/tree/main/fine-tuning-examples).