| from transformers import T5ForConditionalGeneration, T5Tokenizer |
| import gradio as grad |
|
|
| text2text_tkn= T5Tokenizer.from_pretrained("t5-small") |
| mdl = T5ForConditionalGeneration.from_pretrained("t5-small") |
|
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|
|
| def text2text_paraphrase(sentence1,sentence2): |
| inp1 = "mrpc sentence1: "+sentence1 |
| inp2 = "sentence2: "+sentence2 |
| combined_inp=inp1+" "+inp2 |
| enc = text2text_tkn(combined_inp, return_tensors="pt") |
| tokens = mdl.generate(**enc) |
| response=text2text_tkn.batch_decode(tokens) |
| return response |
|
|
| sent1=grad.Textbox(lines=1, label="Sentence1", placeholder="Text in English") |
| sent2=grad.Textbox(lines=1, label="Sentence2", placeholder="Text in English") |
| out=grad.Textbox(lines=1, label="Whether the sentence is acceptable or not") |
| grad.Interface(text2text_paraphrase, inputs=[sent1,sent2], outputs=out).launch() |
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|
