Upload usage.py

usage.py

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+import sys
+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)
+def predict(text):
+    p_spam = clf(text, candidate_labels_spam)["labels"][0]
+    p_urgent = clf(text, candidate_labels_urgent)["labels"][0]
+    return p_spam,p_urgent
+
+
+import pandas as pd
+df = pd.read_csv("test.csv")
+
+texts=df["text"]
+for i in    range( len(texts)):
+     print(texts[i],predict(texts[i]))