Update app.py

app.py

@@ -23,8 +23,8 @@ Customer review classification is a great example of text classification in acti
 The ability to quickly classify sentiment from customers is an added advantage for any business. 
 Therefore, whichever solution you deploy for classifying the customer reviews should deliver results in the shortest time possible. 
 By being fast the solution will process more volume, hence cheaper computational resources are utilized.  
-Deploying a deep learning model to tackle this problem is one solution.
-For this solution, decreasing the model’s latency and increasing its throughput is critical. This is why DeepSparse Pipelines have sparse text classification models. 
+
+When deploying a text classification model, decreasing the model’s latency and increasing its throughput is critical. This is why DeepSparse Pipelines have sparse text classification models. 
 ## Resources 
 [Classify Even Longer Customer Reviews Using Sparsity with DeepSparse](https://neuralmagic.com/blog/accelerate-customer-review-classification-with-sparse-transformers/)
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