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from transformers import T5ForConditionalGeneration, T5Tokenizer |
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import gradio as grad |
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text2text_tkn= T5Tokenizer.from_pretrained("t5-small") |
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mdl = T5ForConditionalGeneration.from_pretrained("t5-small") |
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def text2text_paraphrase(sentence1,sentence2): |
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inp1 = "rte sentence1: "+sentence1 |
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inp2 = "sentence2: "+sentence2 |
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combined_inp=inp1+" "+inp2 |
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enc = text2text_tkn(combined_inp, return_tensors="pt") |
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tokens = mdl.generate(**enc) |
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response=text2text_tkn.batch_decode(tokens) |
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return response |
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sent1=grad.Textbox(lines=1, label="Sentence1", placeholder="Text in English") |
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sent2=grad.Textbox(lines=1, label="Sentence2", placeholder="Text in English") |
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out=grad.Textbox(lines=1, label="Whether sentence2 is deductible from sentence1") |
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grad.Interface(text2text_paraphrase, inputs=[sent1,sent2], outputs=out).launch() |
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