Update app.py

app.py

@@ -32,12 +32,9 @@ def process_input(text_input, labels_or_premise, mode):
         results = {label: score for label, score in zip(prediction['labels'], prediction['scores'])}
         return results, ''
     else:  # NLI mode
-        prediction = nli_classifier([{"text": text_input, "text_pair": labels_or_premise}])[0]
-        results = {
-            "entailment": prediction.get("score", 0) if prediction.get("label") == "entailment" else 0,
-            "contradiction": prediction.get("score", 0) if prediction.get("label") == "contradiction" else 0,
-            "neutral": prediction.get("score", 0) if prediction.get("label") == "neutral" else 0
-        }
+        pred=text_pair='there is a black cat')],return_all_scores=True)
+        results= {pred['label']:pred['score'] for pred in pred}
+
         return results, ''
 
 def update_interface(mode):
@@ -98,19 +95,21 @@ with gr.Blocks() as demo:
             gr.Markdown(label="📈 Analysis", visible=False)
         ]
 
-        with gr.Column(variant="panel") as zero_shot_examples_panel:
+       with gr.Column(variant="panel") as zero_shot_examples_panel:
             gr.Examples(
                 examples=zero_shot_examples,
                 inputs=[text_input, labels_or_premise],
-                label="Zero-Shot Classification Examples"
+                label="Zero-Shot Classification Examples",
+                headers=["Input Text", "Categories"]  # Add headers
             )
-
+    
         with gr.Column(variant="panel") as nli_examples_panel:
             gr.Examples(
                 examples=nli_examples,
                 inputs=[text_input, labels_or_premise],
-                label="Natural Language Inference Examples"
-            )
+                label="Natural Language Inference Examples",
+                headers=["Premise", "Hypothesis"]  # Add headers
+        )
 
     def update_visibility(mode):
         return (