Create app.py

app.py

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+# 📝 Text Summarization Demo | CPU-only HF Space
+
+from transformers import pipeline
+import gradio as gr
+
+# Load a distilled BART summarization model on CPU
+summarizer = pipeline(
+    "summarization",
+    model="sshleifer/distilbart-cnn-12-6",
+    device=-1    # force CPU
+)
+
+def summarize(text: str, max_length: int, min_length: int):
+    if not text.strip():
+        return ""
+    # run the summarization pipeline
+    summary = summarizer(
+        text,
+        max_length=max_length,
+        min_length=min_length,
+        do_sample=False
+    )[0]["summary_text"]
+    return summary
+
+with gr.Blocks(title="📝 Text Summarization") as demo:
+    gr.Markdown(
+        "# 📝 Text Summarizer\n"
+        "Paste in any article, report, or long-form text and get a concise summary—**100% CPU**."
+    )
+
+    with gr.Row():
+        text_in    = gr.Textbox(lines=10, placeholder="Enter your text here…", label="Input Text")
+        max_slider = gr.Slider(20, 200, value=100, step=10, label="Max Summary Length")
+        min_slider = gr.Slider(10, 100, value=30, step=5, label="Min Summary Length")
+
+    run_btn    = gr.Button("Summarize 🔍", variant="primary")
+    summary_out = gr.Textbox(lines=5, label="Summary", interactive=False)
+
+    run_btn.click(
+        summarize,
+        inputs=[text_in, max_slider, min_slider],
+        outputs=summary_out
+    )
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0")