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d449ee2
Create app.py
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app.py
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import torch
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import gradio as gr
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)
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# model_path = ("../Models/models--sshleifer--distilbart-cnn-12-6/snapshots"
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# "/a4f8f3ea906ed274767e9906dbaede7531d660ff")
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# text_summary = pipeline("summarization", model=model_path,
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# torch_dtype=torch.bfloat16)
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# text='''Elon Reeve Musk (/ˈiːlɒn/ EE-lon; born June 28, 1971) is a businessman and investor.
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# He is the founder, chairman, CEO, and CTO of SpaceX; angel investor, CEO, product architect,
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# and former chairman of Tesla, Inc.; owner, executive chairman, and CTO of X Corp.;
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# founder of the Boring Company and xAI; co-founder of Neuralink and OpenAI; and president
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# of the Musk Foundation. He is one of the wealthiest people in the world; as of April 2024,
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# Forbes estimates his net worth to be $178 billion.[4]'''
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# print(text_summary(text));
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def summary (input):
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output = text_summary(input)
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return output[0]['summary_text']
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gr.close_all()
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# demo = gr.Interface(fn=summary, inputs="text",outputs="text")
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demo = gr.Interface(fn=summary,
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inputs=[gr.Textbox(label="Input text to summarize",lines=6)],
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outputs=[gr.Textbox(label="Summarized text",lines=4)],
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title="@GenAILearniverse Project 1: Text Summarizer",
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description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT")
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demo.launch()
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