Update app.py

T5 task grammar check

app.py

@@ -305,20 +305,41 @@
 #-----------------------------------------------------------------------------------
 # 13. Text-to-Text Generation using the T5 model - Task 4 sentiment analysis.
 
+# from transformers import T5ForConditionalGeneration, T5Tokenizer
+# import gradio as grad
+
+# text2text_tkn= T5Tokenizer.from_pretrained("t5-small")
+# mdl = T5ForConditionalGeneration.from_pretrained("t5-small")
+
+# def text2text_sentiment(text):
+#     inp = "sst2 sentence: "+text
+#     enc = text2text_tkn(inp, return_tensors="pt")
+#     tokens = mdl.generate(**enc)
+#     response=text2text_tkn.batch_decode(tokens)
+#     return response
+
+# para=grad.Textbox(lines=1, label="English Text", placeholder="Text in English")
+# out=grad.Textbox(lines=1, label="Sentiment")
+
+# grad.Interface(text2text_sentiment, inputs=para, outputs=out).launch()
+
+#-----------------------------------------------------------------------------------
+# 14. Text-to-Text Generation using the T5 model - Task 5 grammar check.
+
 from transformers import T5ForConditionalGeneration, T5Tokenizer
 import gradio as grad
 
 text2text_tkn= T5Tokenizer.from_pretrained("t5-small")
 mdl = T5ForConditionalGeneration.from_pretrained("t5-small")
 
-def text2text_sentiment(text):
-    inp = "sst2 sentence: "+text
+def text2text_acceptable_sentence(text):
+    inp = "cola sentence: "+text
     enc = text2text_tkn(inp, return_tensors="pt")
     tokens = mdl.generate(**enc)
     response=text2text_tkn.batch_decode(tokens)
     return response
 
 para=grad.Textbox(lines=1, label="English Text", placeholder="Text in English")
-out=grad.Textbox(lines=1, label="Sentiment")
+out=grad.Textbox(lines=1, label="Whether the sentence is acceptable or not")
 
-grad.Interface(text2text_sentiment, inputs=para, outputs=out).launch()
+grad.Interface(text2text_acceptable_sentence, inputs=para, outputs=out).launch()