fix: added link to project

dashboard_featurefinder.py

@@ -70,7 +70,7 @@ def app():
         contrastive learning to project images and caption text onto a common 
         embedding space. We have fine-tuned the model (see [Model card](https://huggingface.co/flax-community/clip-rsicd-v2)) 
         using the RSICD dataset (10k images and ~50k captions from the remote 
-        sensing domain). 
+        sensing domain). Click here for [more information about our project](https://github.com/arampacha/CLIP-rsicd).
         
         This demo shows the ability of the model to find specific features
         (specified as text queries) in the image. As an example, say you wish to

dashboard_image2image.py

@@ -50,7 +50,7 @@ def app():
         contrastive learning to project images and caption text onto a common 
         embedding space. We have fine-tuned the model (see [Model card](https://huggingface.co/flax-community/clip-rsicd-v2)) 
         using the RSICD dataset (10k images and ~50k captions from the remote 
-        sensing domain). 
+        sensing domain). Click here for [more information about our project](https://github.com/arampacha/CLIP-rsicd).
         
         This demo shows the image to image retrieval capabilities of this model, i.e., 
         given an image file name as a query, we use our fine-tuned CLIP model 

dashboard_text2image.py

@@ -30,7 +30,7 @@ def app():
         contrastive learning to project images and caption text onto a common 
         embedding space. We have fine-tuned the model (see [Model card](https://huggingface.co/flax-community/clip-rsicd-v2)) 
         using the RSICD dataset (10k images and ~50k captions from the remote 
-        sensing domain). 
+        sensing domain). Click here for [more information about our project](https://github.com/arampacha/CLIP-rsicd).
         
         This demo shows the image to text retrieval capabilities of this model, i.e., 
         given a text query, we use our fine-tuned CLIP model to project the text query