Seniment.py

app.py

@@ -0,0 +1,22 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the pre-trained model
+classifier = pipeline('sentiment-analysis')
+
+# Define the prediction function
+def predict_sentiment(text):
+    results = classifier(text)
+    return results[0]['label'], results[0]['score']
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=predict_sentiment,
+    inputs="text",
+    outputs=["text", "number"],
+    title="Sentiment Analysis",
+    description="Enter text to classify its sentiment as positive or negative."
+)
+
+# Launch the interface
+iface.launch()