Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+classifier = pipeline('sentiment-analysis', model='distilbert/distilbert-base-uncased-finetuned-sst-2-english')
+
+
+def analyze_sentiment(text):
+    result = classifier(text)
+    # The result is a list of dictionaries, e.g., [{'label': 'POSITIVE', 'score': 0.9998}]
+    # We extract the label and score for better presentation.
+    sentiment_label = result[0]['label']
+    sentiment_score = result[0]['score']
+    return f"Sentiment: {sentiment_label}, Score: {sentiment_score:.2f}"
+
+# Create and launch the Gradio interface
+iface = gr.Interface(
+    fn=analyze_sentiment,
+    inputs='text',
+    outputs='text',
+    title='Sentiment Analysis Application',
+    description='Enter text to get its sentiment (positive/negative) and score.'
+)
+
+
+# Launch the interface
+iface.launch()