`IndexError: list index out of range` when using zeroshot_topic_list in 0.16.1

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Hi, I recently re-ran a notebook for `zeroshot_topic_list` and got the `IndexError: list index our of range`
I fixed this by downgrading to 0.16.0

Full stacktrace:
```
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
Cell In[2], line 18
9 vectorizer_model = CountVectorizer(stop_words="english")
11 topic_model = BERTopic(
12 min_topic_size=20,
13 zeroshot_topic_list=zeroshot_topic_list,
14 zeroshot_min_similarity=.25,
15 vectorizer_model=vectorizer_model
16 )
---> 18 topics, probs = topic_model.fit_transform(docs)
19 topic_model.get_topic_info()

File /opt/conda/lib/python3.10/site-packages/bertopic/_bertopic.py:448, in BERTopic.fit_transform(self, documents, embeddings, images, y)
446 # Combine Zero-shot with outliers
447 if self._is_zeroshot() and len(documents) != len(doc_ids):
--> 448 predictions = self._combine_zeroshot_topics(documents, assigned_documents, assigned_embeddings)
450 return predictions, self.probabilities_

File /opt/conda/lib/python3.10/site-packages/bertopic/_bertopic.py:3682, in BERTopic._combine_zeroshot_topics(self, documents, assigned_documents, embeddings)
3680 cluster_indices = list(documents.Old_ID.values)
3681 cluster_names = list(merged_model.topic_labels_.values())[len(set(y)):]
-> 3682 cluster_topics = [cluster_names[topic + self._outliers] for topic in documents.Topic.values]
3684 df = pd.DataFrame({
3685 "Indices": zeroshot_indices + cluster_indices,
3686 "Label": zeroshot_topics + cluster_topics}
3687 ).sort_values("Indices")
3688 reverse_topic_labels = dict((v, k) for k, v in merged_model.topic_labels_.items())

File /opt/conda/lib/python3.10/site-packages/bertopic/_bertopic.py:3682, in (.0)
3680 cluster_indices = list(documents.Old_ID.values)
3681 cluster_names = list(merged_model.topic_labels_.values())[len(set(y)):]
-> 3682 cluster_topics = [cluster_names[topic + self._outliers] for topic in documents.Topic.values]
3684 df = pd.DataFrame({
3685 "Indices": zeroshot_indices + cluster_indices,
3686 "Label": zeroshot_topics + cluster_topics}
3687 ).sort_values("Indices")
3688 reverse_topic_labels = dict((v, k) for k, v in merged_model.topic_labels_.items())
```

Start in _bertopic.py at fit_transform and _combine_zeroshot_topics, using the reported zeroshot_topic_list notebook configuration to reproduce the failure. Confirm that fitting under 0.16.1 completes without the IndexError and that the returned topics and probabilities remain available.

Written by the indexing model from the issue text.