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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()
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