merve HF staff commited on
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78d6bed
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1 Parent(s): ff6984b

Update app.py

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  1. app.py +1 -1
app.py CHANGED
@@ -10,7 +10,7 @@ st.write("Imagine you're making a chatbot that will answer very general question
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  st.write("If you have very little amount of data, you could actually augment it through language models. There are regex based tools you can use but they tend to create bias due to repetitive patterns, so it's better to use language models for this case. A good model to use is a generative model fine-tuned on Quora Question Pairs dataset. This dataset consists of question pairs that are paraphrase of one another, and T5 can generate a paraphrased question given a source question.")
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  st.write("Try it yourself here πŸ‘‡πŸ»")
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  generator = pipeline("text2text-generation", model = "mrm8488/t5-small-finetuned-quora-for-paraphrasing")
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- default_value = "My basement is in flood, what can I do?"
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  sent = st.text_area("Input", default_value, height = 10)
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  outputs = generator(sent)
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  st.write("Paraphrased Example:")
 
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  st.write("If you have very little amount of data, you could actually augment it through language models. There are regex based tools you can use but they tend to create bias due to repetitive patterns, so it's better to use language models for this case. A good model to use is a generative model fine-tuned on Quora Question Pairs dataset. This dataset consists of question pairs that are paraphrase of one another, and T5 can generate a paraphrased question given a source question.")
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  st.write("Try it yourself here πŸ‘‡πŸ»")
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  generator = pipeline("text2text-generation", model = "mrm8488/t5-small-finetuned-quora-for-paraphrasing")
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+ default_value = "How can I put out grease fire?"
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  sent = st.text_area("Input", default_value, height = 10)
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  outputs = generator(sent)
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  st.write("Paraphrased Example:")