added examples

app.py

@@ -23,7 +23,18 @@ iface = gr.Interface(
     The model was initially pretrained on the [sr-gpt2-large model by Mihailo Škorić](https://huggingface.co/JeRTeh/sr-gpt2-large), 
     then fine-tuned on selected definitions from the Serbian WordNet. Please limit the input to 300 tokens. 
     The outputs represent the Positive (POS), Negative (NEG), and Objective (OBJ) sentiment scores.
-    """
+    """,
+    examples=[
+        ["osoba koja ne prihvata nove ideje"],
+        ["intenzivna ojađenost"],
+        ["uopštenih osećanja tuge"],
+        ["žalostan zbog gubitka ili uskraćenosti"],
+        ["činjenje dobra; osećaj dobrotvornosti"],
+        ["Jako pozitivno osećanje poštovanja i privrežen..."],
+        ["usrećiti ili zadovoljiti"],
+        ["Korisna ili vredna osobina"],
+    ]
+
 )
 
 iface.launch()