'How to save a non tf.Model model and load it with tf.saved_model.load()

I have a trained XGBoost model, and an API that uses tensor flow saved models to load it. Is it possible to save the XGBoost model in a way that will be compatible with saved_model.load().

E.g.

clf = xgb.XGBClassifier()
X_train, y_train = ...
clf.fit(X_train, y_train)
# save the model in some manner that it would work with the next row
model = tf.saved_model.load(model_path)

tensorflow xgboost

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'How to save a non tf.Model model and load it with tf.saved_model.load()

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