email-spam-prediction-function.py

def get_predictions(model, texts):
    # Use the model's tokenizer to tokenize each input text
    docs = [model.tokenizer(text) for text in texts]

    # Use textcat to get the scores for each doc
    textcat = model.get_pipe('textcat')
    scores, _ = textcat.predict(docs)

    # From the scores, find the label with the highest score/probability
    predicted_labels = scores.argmax(axis=1)
    predicted_class = [textcat.labels[label] for label in predicted_labels]

    return predicted_class