Upload food not food text classifier demo from notebook

app.py

@@ -9,7 +9,7 @@ from transformers import pipeline
 def food_not_food_classifier(text: str) -> Dict[str, float]:
   # 2. Setup food not food text classifier
   food_not_food_classifier_pipeline = pipeline(task="text-classification",
-                                      model="adamNLP/learn_hf_food_not_food_text_classifier-distilbert-base-uncased"
+                                      model="adamNLP/learn_hf_food_not_food_text_classifier-distilbert-base-uncased",
                                       batch_size=32,
                                       device="cuda" if torch.cuda.is_available() else "cpu",
                                       top_k=None) # top_k=None => return all possible labels