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
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+pipe = pipeline("summarization", model="sshleifer/distilbart-xsum-1-1", torch_dtype=torch.bfloat16)
+
+# model_path=("../Models/models--sshleifer--distilbart-xsum-1-1/snapshots/891968fcbb0e421075cc2c3dfc8da8d4b24d54a4")
+# text_summary = pipeline("summarization", model=model_path,
+#                 torch_dtype=torch.bfloat16)
+
+"""torch_dtype=torch.bfloat16 this parameter helps in compressing the
+model without compromising the performance"""
+
+text="Elon Reeve Musk (/ˈiːlɒn/ EE-lon; born June 28, 1971) is a businessman known for his leadership of Tesla, SpaceX, and X (formerly Twitter). Since 2025, he has been a senior advisor to United States President Donald Trump and the de facto head of the Department of Government Efficiency (DOGE). Musk is the wealthiest person in the world; as of March 2025, Forbes estimates his net worth to be US$345 billion. He was named Time magazine's Person of the Year in 2021."
+#print(text_summary(text))
+
+"Gradio actually accepts a function, whatever input we give it gives back to the function"
+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="GenAi Text Summarizer",
+                    description="This application is used to create the summary of the text")
+demo.launch(share=True)
+
+
+