Update app.py

app.py

@@ -5,10 +5,17 @@ from transformers import pipeline
 model_name = "Jr0hamza/sentiment-analysis-model"
 sentiment_pipeline = pipeline("text-classification", model=model_name)
 
+# Define custom label mapping
+label_map = {
+    "LABEL_0": "negative",
+    "LABEL_1": "positive"
+}
+
 # Function to predict sentiment
 def predict_sentiment(text):
-    result = sentiment_pipeline(text)
-    return result[0]["label"]
+    result = sentiment_pipeline(text)[0]
+    label = label_map.get(result["label"], "unknown")  # Convert label
+    return f"Sentiment: {label} (Confidence: {result['score']:.2f})"
 
 # Gradio Interface
 interface = gr.Interface(