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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")
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