jaredcodling/tinypara

1import torch2from transformers import PegasusForConditionalGeneration, PegasusTokenizer3 4model_name = 'tuner007/pegasus_paraphrase'5torch_device = 'cuda' if torch.cuda.is_available() else 'cpu'6tokenizer = PegasusTokenizer.from_pretrained(model_name)7model = PegasusForConditionalGeneration.from_pretrained(model_name).to(torch_device)8 9def get_response(input_text,num_return_sequences):10  batch = tokenizer.prepare_seq2seq_batch([input_text],truncation=True,padding='longest',max_length=60, return_tensors="pt").to(torch_device)11  translated = model.generate(**batch,max_length=60,num_beams=10, num_return_sequences=num_return_sequences, temperature=1.5)12  tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)13  return tgt_text14 15from sentence_splitter import SentenceSplitter, split_text_into_sentences16 17splitter = SentenceSplitter(language='en')18 19def paraphraze(text):20  sentence_list = splitter.split(text)21  paraphrase = []22 23  for i in sentence_list:24    a = get_response(i,1)25    paraphrase.append(a)26    paraphrase2 = [' '.join(x) for x in paraphrase]27    paraphrase3 = [' '.join(x for x in paraphrase2) ]28  paraphrased_text = str(paraphrase3).strip('[]').strip("'")29  return paraphrased_text30 31import gradio as gr32def summarize(text):33 34  paraphrased_text = paraphraze(text)35  return paraphrased_text36gr.Interface(fn=summarize, inputs=gr.inputs.Textbox(lines=7, placeholder="Enter text here"), outputs=[gr.outputs.Textbox(label="Paraphrased Text")],examples=[["This Api is the best quillbot api alternative with no words limit."37]]).launch(inline=False)