Update app.py

app.py

@@ -1,21 +1,19 @@
 from transformers import T5ForConditionalGeneration, T5Tokenizer
 import gradio as grad
 
-text2text_tkn= T5Tokenizer.from_pretrained("t5-large")
-mdl = T5ForConditionalGeneration.from_pretrained("t5-large")
+text2text_tkn= T5Tokenizer.from_pretrained("t5-small")
+mdl = T5ForConditionalGeneration.from_pretrained("t5-small")
 
-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
+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 the sentence is acceptable or not")
-
-grad.Interface(text2text_paraphrase, inputs=[sent1,sent2],outputs=out).launch()
+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()