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- "Samica o długości ciała 10–11 mm, szczoteczki na tylnych nogach służące do zbierania pyłku oraz włoski na końcu odwłoka jaskrawo pomarańczowoczerwone. "
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example_title: "Uczenie maszynowe"
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# SHerbert large - Polish SentenceBERT
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SentenceBERT is a modification of the pretrained BERT network that use siamese and triplet network structures to derive semantically meaningful sentence embeddings that can be compared using cosine-similarity. Training was based on the original paper [Siamese BERT models for the task of semantic textual similarity (STS)](https://arxiv.org/abs/1908.10084) with a slight modification of how the training data was used. The goal of the model is to generate different embeddings based on the semantic and topic similarity of the given text.
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- "Samica o długości ciała 10–11 mm, szczoteczki na tylnych nogach służące do zbierania pyłku oraz włoski na końcu odwłoka jaskrawo pomarańczowoczerwone. "
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example_title: "Uczenie maszynowe"
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<img src="https://public.3.basecamp.com/p/rs5XqmAuF1iEuW6U7nMHcZeY/upload/download/VL-NLP-short.png" alt="logo voicelab nlp" style="width:300px;"/>
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# SHerbert large - Polish SentenceBERT
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SentenceBERT is a modification of the pretrained BERT network that use siamese and triplet network structures to derive semantically meaningful sentence embeddings that can be compared using cosine-similarity. Training was based on the original paper [Siamese BERT models for the task of semantic textual similarity (STS)](https://arxiv.org/abs/1908.10084) with a slight modification of how the training data was used. The goal of the model is to generate different embeddings based on the semantic and topic similarity of the given text.
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