sentence bert swedish cased EU AI Act Compliance Profile

KBLab/sentence-bert-swedish-cased

This is a sentence-transformers model: It maps Swedish sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. This model is a bilingual Swedish-English model trained according to instructions in the paper Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation and the documentation accompanying its companion python package. We have used the strongest available pretrained English Bi-Encoder (all-mpnet-base-v2) as a teacher model, and the pretrained Swedish KB-BERT as the student model.

A more detailed description of the model can be found in an article we published on the KBLab blog here and for the updated model here.

Update: We have released updated versions of the model since the initial release. The original model described in the blog post is v1.0. The current version is v2.0. The newer versions are trained on longer paragraphs, and have a longer max sequence length. v2.0 is trained with a stronger teacher model and is the current default.

| Model version | Teacher Model | Max Sequence Length | |---------------|---------|----------| | v1.0 | paraphrase-mpnet-base-v2 | 256 | | v1.1 | paraphrase-mpnet-base-v2 | 384 | | v2.0 | all-mpnet-base-v2 | 384 |

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