Update app.py

app.py

@@ -72,4 +72,26 @@ else:
         description="Enter a sentence with a [MASK] token to see the model's prediction."
     )
 
+# --- Step 4: Launch the Gradio App --- #
+
+import gradio as gr
+from transformers import pipeline
+
+# Load a small, efficient model
+generator = pipeline("text-generation", model="distilgpt2")
+
+def generate_text(prompt):
+    result = generator(prompt, max_length=50, num_return_sequences=1)
+    return result[0]["generated_text"]
+
+demo = gr.Interface(
+    fn=generate_text,
+    inputs="text",
+    outputs="text",
+    title="Simple LLM Demo",
+    description="A lightweight text generation app using DistilGPT2."
+)
+
+# Keep the app alive on Hugging Face Spaces
+demo.launch(server_name="0.0.0.0", server_port=7860)