Value Error when tuning MaximalMarginalRelevance

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### Desribe the bug

I am trying do some representation model hyperparameter tuning on a BERTopic model by altering the diversity parameter in MaximalMarginalRelevance.

I am setting top_n_words in MMR as the same as the topic model. However, I keep encountering

`ValueError: Length of weights not compatible with specified axis.`

in certain trials when running `update_topics`.

It is only happening due to the MMR part (with removal the code works fine), and happens randomly for certain trials between runs. Do you know why this might be happening?

I am using v0.16.4.

### Reproduction

```python
from bertopic import BERTopic
import optuna
import copy
def _execute_representation_tuning(
self, topic_model: BERTopic, docs: List[str]
) -> Callable:
"""
Execute BERTopic topic representation tuning using Optuna.

Args:
topic_model (BERTopic): Fit topic model to optimize
docs (List[str]): Documents from which to extract topics

Returns:
(Callable) Objective function execution for trial.
"""
def _inner_objective(trial: optuna.trial.Trial) -> float:
"""
Objective function for Optuna.
"""

topic_model_copy = copy.deepcopy(topic_model)
top_n_words = topic_model_copy.top_n_words

ctfidf_model = ClassTfidfTransformer(
reduce_frequent_words=trial.suggest_categorical(
"reduce_frequent_words",
[True, False],
),
bm25_weighting=trial.suggest_categorical(
"bm25_weighting", [True, False]
),
)

mmr = MaximalMarginalRelevance(
diversity=trial.suggest_float(
"diversity",
0.1,
0.9,
),
top_n_words=top_n_words,
)

topic_model_copy.update_topics(
docs=docs,
top_n_words=top_n_words,
ctfidf_model=ctfidf_model,
representation_model=mmr,
)

score = ...scorer function...

return score

return _inner_objective
```

### BERTopic Version

0.16.4

Start with the update_topics call and the MaximalMarginalRelevance configuration in the reproduction, then run the provided tuning example across trials to isolate when the ValueError occurs. Trace the representation update and weighting inputs involved in those trials; done means update_topics completes for the reported MMR settings without the incompatible-weights error.

Written by the indexing model from the issue text.