zeroonesfas

How to make predictions by retrieval models with multiple features?

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` class UserModel(tf.keras.Model): def __init__(self,use_timestamps,use_distance): super().__init__() self._use_timestamps = use_timestamps self._use_distance = use_distance self.user_embedding = tf.keras.Sequential([ tf.keras.layers.StringLookup( vocabulary=unique_user_ids, mask_token=None), tf.keras.layers.Embedding(len(unique_user_ids) + 1, 32) ]) max_tokens = 10_000 self.Preference1_embedding = tf.keras.Sequential([ tf.keras.layers.StringLookup(...

I trained a retrieval model but the model recommended items that were used by the user before. Do you guys have any ways to make sure that the recommended items...