Update usage.py

usage.py

@@ -4,10 +4,8 @@ from transformers import pipeline
 # Define candidate labels for classification
 candidate_labels_spam = ['Spam', 'not Spam']
 candidate_labels_urgent = ['Urgent', 'not Urgent']
-
-model="MoritzLaurer/deberta-v3-large-zeroshot-v1.1-all-33"
 model="SpamUrgencyDetection"
-clf = pipeline("zero-shot-classification", model=model)
+clf = pipeline("zero-shot-classification", model=model) 32
 def predict(text):
     p_spam = clf(text, candidate_labels_spam)["labels"][0]
     p_urgent = clf(text, candidate_labels_urgent)["labels"][0]