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)
+
+# For Local we can use this only
+# text = "Elon Reeve Musk FRS (/ˈiːlɒn/; born June 28, 1971) is a businessman known for his key roles in the space company SpaceX and the automotive company Tesla, Inc. His other involvements include ownership of X Corp., the company that operates the social media platform X (formerly Twitter), and his role in the founding of the Boring Company, xAI, Neuralink, and OpenAI. Musk is the wealthiest individual in the world; as of November 2024, Forbes estimates his net worth to be US$323 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=[gr.Textbox(label="Input text to summarize", lines=6)], 
+                    outputs=[gr.Textbox(label="Summarized text", lines=10)],
+                    title = "Gen AI Text Summarization",
+                    description= "Enter details text the tool will give you summarized text"
+                    )
+demo.launch(share=True)