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from transformers import AutoTokenizer, AutoModelWithLMHead | |
import gradio as grad | |
text2text_tkn = AutoTokenizer.from_pretrained("deep-learning-analytics/wikihow-t5-small") | |
mdl = AutoModelWithLMHead.from_pretrained("deep-learning-analytics/wikihow-t5-small") | |
def text2text_summary(para): | |
initial_txt = para.strip().replace("\n","") | |
tkn_text = text2text_tkn.encode(initial_txt,return_tensors="pt") | |
tkn_ids = mdl.generate(tkn_text,max_length=250,num_beams=5,repetition_penalty=2.5, early_stopping=True) | |
response = text2text_tkn.decode(tkn_ids[0],skip_special_tokens=True) | |
return response | |
para = grad.Textbox(lines=10, label="Paragraph",placeholder="Copy paragraph") | |
out = grad.Textbox(lines=1, label="Summary") | |
grad.Interface(text2text_summary, inputs=para, outputs=out).launch() | |