Update app.py

app.py

@@ -1,20 +1,26 @@
-
 from transformers import pipeline
 import gradio as gr
 
-human_read={"LABEL_0":"Negative",
-            "LABEL_1":"Positive"}
-sentimental=pipeline("text-classification", model="Dmyadav2001/Sentimental-Analysis")
+# Label mapping
+human_read = {"LABEL_0": "Negative", "LABEL_1": "Positive"}
+
+# Load model
+sentimental = pipeline("text-classification", model="Dmyadav2001/Sentimental-Analysis")
+
+# Prediction function
 def predictive_model(texts):
-  result=sentimental(texts)
-  sentiment=human_read[result[0]["label"]]
-  score=result[0]["score"]
-  return sentiment, score
+    result = sentimental(texts)
+    sentiment = human_read[result[0]["label"]]
+    score = result[0]["score"]
+    return sentiment, score
+
+# Gradio Interface
+interface = gr.Interface(
+    fn=predictive_model,
+    inputs="text",
+    outputs=["text", "number"],
+    title="Sentiment-Analysis-App",
+    description="Give your text, and my model will predict whether it's Positive or Negative."
+)
 
-interface=gr.Interface(fn=predictive_model,
-                      inputs="text",
-                      outputs=["text","number"],
-                      title="Sentiment-Analysis-App",
-                      description="Gave your text my machine is going to detect Positive / Negative "
-                      )
-interface.launch()
+interface.launch()