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Update app.py
Browse filesT5 task sentence paraphrasing
app.py
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@@ -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
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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
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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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out=grad.Textbox(lines=1, label="Whether the sentence is acceptable or not")
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grad.Interface(
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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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# 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_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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#-----------------------------------------------------------------------------------
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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()
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