Update app.py

app.py

@@ -177,7 +177,9 @@ def predict_inverse(hardness_original_target, ys_original_target, request: gr.Re
     for c in optimized_x.columns:
         if c in continuous_variables:
             if c in ['PROPERTY: Calculated Density (g/cm$^3$)', 'PROPERTY: Calculated Young modulus (GPa)']:
-                optimized_x[c]=optimized_x[c]*(scaling_factors[c][1]-scaling_factors[c][0])+scaling_factors[c][0]
+                optimized_x[c]=round(optimized_x[c]*(scaling_factors[c][1]-scaling_factors[c][0])+scaling_factors[c][0], 2)
+            else:
+                optimized_x[c] = round(optimized_x[c], 2)
     result = optimized_x
     result = result[result>0.0].dropna(axis=1)