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  This is a [sentence-transformers](https://www.SBERT.net) model that maps personality-related items or texts into a 768-dimensional dense vector space and can be used for many tasks in personality psychology.
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- The model has been generated by fine-tuning [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) using unsigned empirical correlations of 200k pairs of personality items. As a result, the model encodes the content of personality-related texts independent of the direction (e.g., negation).
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  See [Wulff & Mata (2024)](https://osf.io/preprints/psyarxiv/9h7aw) (see [Supplement](https://osf.io/z47qs/)) for details. For a similar approach, see [Hommel & Arslan (2024)](https://osf.io/preprints/psyarxiv/kjuce).
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  This is a [sentence-transformers](https://www.SBERT.net) model that maps personality-related items or texts into a 768-dimensional dense vector space and can be used for many tasks in personality psychology.
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+ The model has been generated by fine-tuning [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) using unsigned empirical correlations of 200k pairs of personality items. The model, therefore, encodes the content of personality-related texts independent of the direction (e.g., negation).
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  See [Wulff & Mata (2024)](https://osf.io/preprints/psyarxiv/9h7aw) (see [Supplement](https://osf.io/z47qs/)) for details. For a similar approach, see [Hommel & Arslan (2024)](https://osf.io/preprints/psyarxiv/kjuce).
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