Create app.py

app.py

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+import torch
+import gradio as gr
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+text_summarize = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
+
+
+def summary(input_text):
+    output_text = text_summarize(input_text)
+    return output_text[0]['summary_text']
+
+
+gr.close_all()
+
+# demo = gr.Interface(fn=summary, inputs="text", outputs="text")
+demo = gr.Interface(fn=summary,
+                    inputs=[gr.Textbox(label="Input text to summarize", lines=10)],
+                    outputs=[gr.Textbox(label="Summarized text", lines=5)])
+
+demo.launch()
+
+