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app.py

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+import gradio as gr
+from transformers import pipeline
+
+model_name = "cardiffnlp/twitter-roberta-base-sentiment-latest"
+
+def analyze_sentiment(text):
+    classifier = pipeline('sentiment-analysis', model=model_name, use_auth_token=None)
+    result = classifier(text)
+    return [{"label": res['label'], "score": f"{res['score']:.2f}"} for res in result]
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Sentiment Analyzer")
+    gr.Markdown("Powered by cardiffnlp/twitter-roberta-base-sentiment-latest")
+    text_input = gr.Textbox(label="Text", placeholder="Enter text to analyze...")
+    output = gr.JSON(label="Sentiment Result")
+    btn = gr.Button("Analyze")
+    btn.click(fn=analyze_sentiment, inputs=text_input, outputs=output)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+transformers
+torch