run480 commited on
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db5817e
1 Parent(s): 17f7791

Update app.py

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T5 task sentence paraphrasing

Files changed (1) hide show
  1. app.py +30 -6
app.py CHANGED
@@ -324,7 +324,28 @@
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  # grad.Interface(text2text_sentiment, inputs=para, outputs=out).launch()
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  #-----------------------------------------------------------------------------------
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- # 14. Text-to-Text Generation using the T5 model - Task 5 grammar check.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  from transformers import T5ForConditionalGeneration, T5Tokenizer
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  import gradio as grad
@@ -332,14 +353,17 @@ import gradio as grad
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  text2text_tkn= T5Tokenizer.from_pretrained("t5-small")
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  mdl = T5ForConditionalGeneration.from_pretrained("t5-small")
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- def text2text_acceptable_sentence(text):
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- inp = "cola sentence: "+text
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- enc = text2text_tkn(inp, return_tensors="pt")
 
 
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  tokens = mdl.generate(**enc)
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  response=text2text_tkn.batch_decode(tokens)
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  return response
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- para=grad.Textbox(lines=1, label="English Text", placeholder="Text in English")
 
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  out=grad.Textbox(lines=1, label="Whether the sentence is acceptable or not")
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- grad.Interface(text2text_acceptable_sentence, inputs=para, outputs=out).launch()
 
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  # grad.Interface(text2text_sentiment, inputs=para, outputs=out).launch()
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  #-----------------------------------------------------------------------------------
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+ # 14. Text-to-Text Generation using the T5 model - Task 5 grammar check - this doesn't work great unfortunately.
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+
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+ # from transformers import T5ForConditionalGeneration, T5Tokenizer
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+ # import gradio as grad
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+
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+ # text2text_tkn= T5Tokenizer.from_pretrained("t5-small")
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+ # mdl = T5ForConditionalGeneration.from_pretrained("t5-small")
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+
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+ # def text2text_acceptable_sentence(text):
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+ # inp = "cola sentence: "+text
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+ # enc = text2text_tkn(inp, return_tensors="pt")
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+ # tokens = mdl.generate(**enc)
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+ # response=text2text_tkn.batch_decode(tokens)
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+ # return response
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+
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+ # para=grad.Textbox(lines=1, label="English Text", placeholder="Text in English")
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+ # out=grad.Textbox(lines=1, label="Whether the sentence is acceptable or not")
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+
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+ # grad.Interface(text2text_acceptable_sentence, inputs=para, outputs=out).launch()
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+
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+ #-----------------------------------------------------------------------------------
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+ # 15. Text-to-Text Generation using the T5 model - Task 6 sentence paraphasing
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  from transformers import T5ForConditionalGeneration, T5Tokenizer
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  import gradio as grad
 
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  text2text_tkn= T5Tokenizer.from_pretrained("t5-small")
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  mdl = T5ForConditionalGeneration.from_pretrained("t5-small")
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+ def text2text_paraphrase(sentence1,sentence2):
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+ inp1 = "mrpc sentence1: "+sentence1
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+ inp2 = "sentence2: "+sentence2
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+ combined_inp=inp1+" "+inp2
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+ enc = text2text_tkn(combined_inp, return_tensors="pt")
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  tokens = mdl.generate(**enc)
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  response=text2text_tkn.batch_decode(tokens)
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  return response
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+ sent1=grad.Textbox(lines=1, label="Sentence1", placeholder="Text in English")
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+ sent2=grad.Textbox(lines=1, label="Sentence2", placeholder="Text in English")
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  out=grad.Textbox(lines=1, label="Whether the sentence is acceptable or not")
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+ grad.Interface(text2text_paraphrase, inputs=[sent1,sent2], outputs=out).launch()