hey @olaffson, as described in the sentencebert paper 3 uses a siamese network structure to learn the sentence embeddings.

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in general, this approach gives higher-quality embeddings than those you’d get from distilbert etc and you can find a nice performance chart here 5
regarding your second question, i’m not sure which api you’re referring to exactly in the blog post (which is mostly about the integration of sentence-transformers with the hugging face hub). but indeed, once you have the embeddings you can compute metrics / cluster using whatever tools you wish