Suggestion & Feedback: Add support for Apple Silicons' GPU support

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First of all thanks a lot for this amazing package! I am currently using a MacBook Pro 2021 version with M1 Pro chip. As many Apple users may know, PyTorch now supports GPU acceleration by using mps as computing device. However, currently in the BERTopic model, there is no support for this parameter.

After digging into the details for some time I found a easy work around: SentenceTransformer do supports the device parameter, so we can simply do the following:

`embedding = SentenceTransformer('paraphrase-multilingual-MiniLM-L12-v2', device = 'mps')`

`model = BERTopic(language="chinese (simplified)", embedding_model=embedding, nr_topics='auto',verbose=True, vectorizer_model=vectorizer,) `

which will perform exactly as the default model if an user chooses to. On my Mac, this drastically reduce the training time from 4h30m to 58m.

I assume this should be also easy to incorporate into the package, which will be very helpful. Thanks!

Start by locating BERTopic's embedding model handling and how it interacts with SentenceTransformer. Check how a device such as `mps` could be supported while preserving the default behavior, then verify topic-model training with Apple Silicon GPU acceleration.

Written by the indexing model from the issue text.