Uploading food not food text classifier demo app.py

app.py

@@ -6,7 +6,7 @@ from typing import TypedDict
 from transformers import pipeline
 
 # Create function to use our model on given text
-def food_not_food_classifier(text: str) -> Dict[str, float]:
+def food_not_food_classifier(text: str) -> dict[str, float]:
     food_not_food_classifier = pipeline(task="text-classifcation",
                                          # 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",