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Update app.py
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app.py
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import gradio as gr
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import gradio as gr
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import transformers
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from transformers import BartTokenizer, BartForConditionalGeneration
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import spaces
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model_name = 'Karzan/bart-summarization'
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tokenizer = BartTokenizer.from_pretrained(model_name)
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model = BartForConditionalGeneration.from_pretrained(model_name)
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@spaces.GPU(duration=120)
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def summarize(inp):
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inp = inp.replace('\n','')
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inp = tokenizer.encode(inp, return_tensors='pt', max_length=1024)
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summary_ids = model.generate(inp, num_beams=4, max_length=150, early_stopping=True)
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summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
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return summary
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gr.Interface(fn=summarize, inputs=gr.inputs.Textbox(lines=7, label="Input Text"), outputs="text").launch(inline=False)
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