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="shleifer/distilbart-cnn-12-6",
+                        torch_dtype=torch.bfloat16)
+# model_path = ("../Models/models--sshleifer--distilbart-cnn-12-6/snapshots/"
+#              "a4f8f3ea906ed274767e9906dbaede7531d660ff")
+# text_summary = pipeline("summarization", model=model_path,
+#                         torch_dtype=torch.bfloat16)
+
+# text = '''Elon Reeve Musk (/ˈiːlɒn/ EE-lon; born June 28, 1971) is a businessman and investor.
+# # He is the founder, chairman, CEO, and CTO of SpaceX; angel investor, CEO, product architect,
+# # and former chairman of Tesla, Inc.; owner, executive chairman, and CTO of X Corp.;
+# # founder of the Boring Company and xAI; co-founder of Neuralink and OpenAI; and president
+# # of the Musk Foundation. He is one of the wealthiest people in the world; as of April 2024,
+# # Forbes estimates his net worth to be $178 billion.[4]'''
+# 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="Summarized text",lines=4)],
+                    title="@GenAILearniverse Project 1: Text Summarizer",
+                    description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT")
+demo.launch()