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="ainize/bart-base-cnn",torch_dtype = torch.bfloat16)
+
+
+
+# text ='''Elon Reeve Musk FRS  is an international businessman and entrepreneur known for his leadership of Tesla, SpaceX, X (formerly Twitter), and the Department of Government Efficiency (DOGE). Musk has been the wealthiest person in the world since 2021; as of May 2025, Forbes estimates his net worth to be US$424.7 billion.'''
+
+# print(text_summary(text))
+
+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="summarization",lines=4)],
+                    title="Text Summarization",
+                    description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT")
+
+
+demo.launch()