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
+
+text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6",
+                torch_dtype = torch.bfloat16, device=0)
+
+def summary (input):
+    output = text_summary(input)
+    return output[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 the text to summarize")],
+                    outputs=[gr.Textbox(label="Summarized text")],
+                    title="Text summarizer",
+                    )
+demo.launch()
+
+