| from transformers import pipeline | |
| generator = pipeline('text-generation', model='EleutherAI/gpt-neo-2.7B') | |
| def query(input_sentence,num,start): | |
| string3=[] | |
| for i in range(0,num): | |
| intial="""These are the few examples of converting original sentences into paraphrased sentences.\n original: Symptoms of influenza include fever and nasal congestion.\n paraphrase: A stuffy nose and elevated temperature are signs you may have the flu.\n original: Maintaining a creative work environment is not only beneficial to employees, but also to company profits.\n paraphrase: Having a fertile work environment can increase productivity and profitability.\n """ | |
| full_input=intial+"original:"+input_sentence + "\n paraphrase:"+start | |
| string1=generator("EleutherAI has", do_sample=True, min_length=len(full_input.split()))[0]['generated_text'] | |
| string2=string1.split('paraphrase:',3)[-1] | |
| string3.append(string2.split('.',1)[0]+".") | |
| return '\n\n'.join([i for i in string3[0:]]) | |
| title = "Paraphrasing" | |
| description = "Gradio Demo for Paraphrasing" | |
| gr.Interface(fn=query, inputs=[gr.inputs.Textbox(lines=4, label="Input Text (Single Sentence)"),gr.inputs.Slider( minimum=1, maximum=10, step=1, default=4, label="Numbers of Outputs"),gr.inputs.Textbox(lines=1, label="Starting Point (optional)")],outputs=["text"],title=title,description=description,enable_queue=True).launch() |