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)
+
+
+
+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 text to summarize",lines=6)],
+                    outputs=[gr.Textbox(label="Summarized text",lines=4)],
+                    title=" Testing_Text_Summarizer: Text Summarizer",
+                    description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT")
+demo.launch()
+
+