Update my_model/tabs/home.py

my_model/tabs/home.py

@@ -48,7 +48,7 @@ def run_home() -> None:
                 Unlike other vision-language tasks, VQA requires many Computer Vision sub-tasks to be solved in the process, 
                 including: **Object recognition**, **Object detection**, **Attribute classification**, **Scene 
                 classification**, **Counting**, **Activity recognition**, **Spatial relationships among objects**, 
-                and **Commonsense reasoning**. These VQA tasks often do not require external factual knowledge and only 
+                and **Common-sense reasoning**. These VQA tasks often do not require external factual knowledge and only 
                 in rare cases require common-sense reasoning. Furthermore, VQA models cannot derive additional knowledge 
                 from existing VQA datasets should a question require it, therefore **Knowledge-Based Visual Question 
                 Answering (KB-VQA)** has been introduced. KB-VQA is a relatively new extension to VQA with datasets