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  <img src="https://cdn-uploads.huggingface.co/production/uploads/60bccec062080d33f875cd0c/38Yc1IgU4bH92Wyb43J2I.png" alt="image/png" style="max-width: 75%;">
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  This [Sentence Transformer Model] (https://www.SBERT.net) converts sentences and paragraphs into a 768-dimensional vector space suitable for tasks such as clustering and semantic search.
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- - This model focuses on the similarity of long documents; use it for comparing embeddings of long text documents
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  - For more info, see the `pszemraj/synthetic-text-similarity` dataset used for training
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  - Pre-trained and tuned for a context length of 16,384
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  - This initial version may be updated in the future.
 
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  <img src="https://cdn-uploads.huggingface.co/production/uploads/60bccec062080d33f875cd0c/38Yc1IgU4bH92Wyb43J2I.png" alt="image/png" style="max-width: 75%;">
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  This [Sentence Transformer Model] (https://www.SBERT.net) converts sentences and paragraphs into a 768-dimensional vector space suitable for tasks such as clustering and semantic search.
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+ - This model focuses on the similarity of long documents; use it for comparing embeddings of long text documents
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  - For more info, see the `pszemraj/synthetic-text-similarity` dataset used for training
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  - Pre-trained and tuned for a context length of 16,384
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  - This initial version may be updated in the future.