Update app.py

app.py

@@ -8,7 +8,7 @@ DeepSparse is sparsity-aware inference runtime offering GPU-class performance on
 The text classification Pipeline, for example, wraps an NLP model with the proper preprocessing and postprocessing pipelines, such as tokenization. Here is sample code for a text classification pipeline: 
 ```
 from deepsparse import Pipeline
-pipeline = Pipeline.create(task=task, model_path="zoo:nlp/text_classification/distilbert-none/pytorch/huggingface/mnli/pruned80_quant-none-vnni",model_scheme="mnli",model_config={"hypothesis_template": "This text is related to {}"},)
+pipeline = Pipeline.create(task="zero_shot_text_classification", model_path="zoo:nlp/text_classification/distilbert-none/pytorch/huggingface/mnli/pruned80_quant-none-vnni",model_scheme="mnli",model_config={"hypothesis_template": "This text is related to {}"},)
 inference = pipeline(sequences= text,labels=['politics', 'public health', 'Europe'],)
 print(inference)
 ```