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app.py

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+from transformers import T5ForConditionalGeneration, T5Tokenizer
+import gradio as grad
+
+text2text_tkn= T5Tokenizer.from_pretrained("t5-small")
+mdl = T5ForConditionalGeneration.from_pretrained("t5-small")
+
+
+
+def text2text_deductible(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_ deductible, inputs=[sent1,sent2], outputs=out).launch()

requirements.txt

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+gradio
+transformers
+torch
+transformers[sentencepiece]