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README.md
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@@ -61,7 +61,7 @@ The [KeyBERT homepage](https://github.com/MaartenGr/KeyBERT) provides other seve
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## Topic Modeling
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To analyse a group of documents and determine the topics, has a lot of use cases. [BERTopic](https://github.com/MaartenGr/BERTopic) combines the power of sentence transformers with c-TF-IDF to create clusters for easily interpretable topics.
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It would take too much time to explain topic modeling here. Instead we recommend that you take a look at the link above, as well as the [
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```python
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topic_model = BERTopic(embedding_model='NbAiLab/nb-sbert').fit(docs)
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## Topic Modeling
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To analyse a group of documents and determine the topics, has a lot of use cases. [BERTopic](https://github.com/MaartenGr/BERTopic) combines the power of sentence transformers with c-TF-IDF to create clusters for easily interpretable topics.
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It would take too much time to explain topic modeling here. Instead we recommend that you take a look at the link above, as well as the [documentation](https://maartengr.github.io/BERTopic/index.html). The main adaptation you would need to do to use the Norwegian nb-sbert, is to add the following:
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```python
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topic_model = BERTopic(embedding_model='NbAiLab/nb-sbert').fit(docs)
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