Comment by VHRanger

3 years ago

You can find some comparisons and evaluation datasets/tasks here: https://www.sbert.net/docs/pretrained_models.html

Generally MiniLM is a good baseline. For faster models you want this library:

https://github.com/oborchers/Fast_Sentence_Embeddings

For higher quality ones, just take the bigger/slower models in the SentenceTransformers library

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VHRanger

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sroussey  3 years ago

Is there performance comparisons for Apple Silicon machines?

  • VHRanger  3 years ago

    Performance in terms of model quality would be the same.

    The fast-se library uses C++ code and word embeddings being averaged to generate sentence embeddings, so would be similarly fast, or faster on apple silicon than x86.

    For the SentenceTransformer library models I'm not sure, but I think it would run off the CPU for a M1/M2 computer