Multilingual Sentence-BERT Model

We learned how to make the monolingual model multilingual through knowledge distillation. Now let's learn how to use the pre-trained multilingual model. The researchers have made their pre-trained models publicly available with the sentence-transformers library. So, we can directly download a pre-trained model and use it for our task.

Pre-trained multilingual models

The available pre-trained multilingual models are as follows:

• distiluse-base-multilingual-cased: This supports Arabic, Chinese, Dutch, English, French, German, Italian, Korean, Polish, Portuguese, Russian, Spanish, and Turkish.

• xlm-r-base-en-ko-nli-ststb: This supports Korean and English.

• xlm-r-large-en-ko-nli-ststb: This supports Korean and English.

Now, let's learn how to use these pre-trained models.

Using the multilingual model

Let's see how to compute the similarity between two sentences in a different language. First, let's import the SentenceTransformer module: