metric= "cosine" error reported

Nobody has claimed this yet.

### Have you searched existing issues? 🔎

- [X] I have searched and found no existing issues

### Desribe the bug

I wanted to set cosine to represent the distance parameter when I personalized hdbscan. This instantiation didn't go wrong, but I passed the instantiation hdbscan_model into BERTopic(). Unrecognized metric 'cosine'

### Reproduction

```python
from bertopic import BERTopic
hdbscan_model = HDBSCAN(
min_cluster_size=200,，
min_samples=20,
metric='cosine',
prediction_data=True
)
topic_model = BERTopic(embedding_model=transformer_model,
#min_topic_size=3,
verbose=True,
umap_model=umap_model,
hdbscan_model=hdbscan_model,
ctfidf_model=ctfidf_model,
representation_model=representation_model,
#top_n_words=10,
#min_topic_size=10,
#nr_topics=None,
#low_memory=False,
#calculate_probabilities=True
)
topics,probs=topic_model.fit_transform(sentences,embeddings=embeddings)
```

### BERTopic Version

0.16.4

Start by running the supplied HDBSCAN and BERTopic reproduction with BERTopic 0.16.4, focusing on where the custom hdbscan_model is accepted during fit_transform. Trace the handling of the metric='cosine' configuration and compare the reported error with HDBSCAN's supported metrics. Done means cosine works through this integration or the incompatibility is clearly reported and covered by a regression test.

Written by the indexing model from the issue text.