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from transformers import AutoModelWithLMHead, AutoTokenizer
import gradio as grad
text2text_tkn = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
mdl = AutoModelWithLMHead.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
def text2text(context,answer):
input_text = "answer: %s context: %s </s>" % (answer, context)
features = text2text_tkn ([input_text], return_tensors='pt')
output = mdl.generate(input_ids=features['input_ids'],
attention_mask=features['attention_mask'],
max_length=64)
response=text2text_tkn.decode(output[0])
return response
context=grad.Textbox(lines=10, label="English", placeholder="Context")
ans=grad.Textbox(lines=1, label="Answer")
out=grad.Textbox(lines=1, label="Genereated Question")
grad.Interface(text2text, inputs=[context,ans], outputs=out).launch()
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