Uploading food not food text classifier demo app.py

app.py

@@ -7,7 +7,7 @@ from transformers import pipeline
 
 # Create function to use our model on given text
 def food_not_food_classifier(text: str) -> dict[str, float]:
-    food_not_food_classifier = pipeline(task="text-classifcation",
+    food_not_food_classifier = pipeline(task="text-classification",
                                          # Because our model is on Hugging Face already, we can pass in the model name directly
                                         model="mrdbourke/learn_hf_food_not_food_text_classifier-distilbert-base-uncased",
                                         device="cuda" if torch.cuda.is_available() else "cpu",