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(task="summarization", model= "sshleifer/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 known for his key roles in Tesla, Inc., SpaceX, and Twitter (which he rebranded as X). Since 2025, he has been a senior advisor to United States president Donald Trump and de facto head of the Department of Government Efficiency (DOGE). Musk is the wealthiest person in the world; as of February 2025, Forbes estimates his net worth to be US$353 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="Summarized text", lines=4)],
+                    title="TEXT SUMMARIZER",
+                    description="THIS APPLICATION WILL BE USED TO SUMMARIZE TEXT")
+demo.launch()