Comment by fzliu

I would not use word2vec in any application today - I used it in the blog post because it's a well-known model and because the embeddings it generates are static, i.e. one token always maps to the same embedding regardless of context.

If you want to create embeddings at the sentence level, a good place to start is SBERT: https://www.sbert.net/