commit

sample.py

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+from transformers import pipeline
+
+def classify_text(email):
+    """
+    Use Facebook BART model to classify an email into "spam" or "not spam"
+    
+    Args:
+        email (str): The email to classify
+    
+    Returns:
+        str: The classification of the email ("spam" or "not spam")
+    """
+    # Load the BART model for text classification
+    classifier = pipeline(task="zero-shot-classification", model="facebook/bart-large-mnli")
+
+    # Classify the email
+    labels = ['spam','not spam']
+    template = 'This email is {}.'
+    result = classifier(email, labels)
+
+    # Get the label with the highest score
+    label = result['labels'][0]
+
+    return label
+
+classify_text('hi I am marketer, we have good product for your good life')