Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the summarization pipeline with the facebook/bart-large-cnn model
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Define the summarization function
+def summarize(text):
+    # Generate summary with min_length=10 and max_length=100 tokens
+    summary = summarizer(text, min_length=10, max_length=100)
+    # Extract and return the summarized text
+    return summary[0]['summary_text']
+
+# Define input and output components with clear labels
+inputs = gr.Textbox(label="Input Text", lines=10)
+outputs = gr.Textbox(label="Summary")
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=summarize,
+    inputs=inputs,
+    outputs=outputs,
+    title="Text Summarizer",
+    description="Enter a long piece of text and get a summary using the BART model."
+)
+
+# Launch the interface
+iface.launch()