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app.py
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import os
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import gradio as gr
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from transformers import pipeline
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def blog_gen(txt):
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generator=pipeline(task='text-generation',model='gpt2')
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gen_blog=generator(txt,max_length=300,num_return_sequences=2)
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remove_gen_text = list(map(lambda x: x["generated_text"], gen_blog))
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clean_text = list(map(lambda x: x.replace("\n\n", " "), remove_gen_text))
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return clean_text
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iface = gr.Interface(fn=blog_gen,
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inputs=[
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gr.inputs.Textbox(
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lines=2, placeholder=None, label='Sentence'),
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],
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outputs=[gr.outputs.JSON(label=None)])
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iface.launch(
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