| from transformers import T5ForConditionalGeneration, T5Tokenizer | |
| import gradio as grad | |
| text2text_tkn= T5Tokenizer.from_pretrained("t5-small") | |
| mdl = T5ForConditionalGeneration.from_pretrained("t5-small") | |
| def text2text_paraphrase(sentence1,sentence2): | |
| inp1 = "rte 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 sentence2 is deductible from sentence1") | |
| grad.Interface(text2text_paraphrase, inputs=[sent1,sent2], outputs=out).launch() | |