MalteHB/-l-ctra
Ælæctra was created as part of a Cognitive Science bachelor thesis, in the attempt to enhance the Danish NLP community with a more efficient Transformer-based language model.
This project offers a specialized language model designed to process Danish text more efficiently than existing options. It takes raw Danish text as input and helps identify and extract specific entities within that text, such as names, locations, or organizations. Developers and researchers working with Danish natural language processing applications would find this model particularly useful.
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Use this if you need a language model specifically optimized for Danish text analysis that is computationally less demanding than other large models.
Not ideal if your primary concern is absolute state-of-the-art accuracy on all NLP tasks, as it may score slightly lower than larger models, or if you are not working with Danish text.
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Jupyter Notebook
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MIT
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Last pushed
Oct 31, 2022
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