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  The model has been trained on a collection of 28k news articles with tags. Its purpose is to create tags suitable for the given article. We can use this model also for information-retrieval purposes (GenQ), fine-tuning sentence-transformers for asymmetric semantic search.
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  <p align="center">
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  <img src="https://upload.wikimedia.org/wikipedia/commons/1/1a/Pieter_Bruegel_d._%C3%84._066.jpg" width="600"> </br>
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  Pieter Bruegel the Elder, The Fight Between Carnival and Lent, 1559
 
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  The model has been trained on a collection of 28k news articles with tags. Its purpose is to create tags suitable for the given article. We can use this model also for information-retrieval purposes (GenQ), fine-tuning sentence-transformers for asymmetric semantic search.
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+ If you like this project, consider supporting it with a cup of coffee! 🤖✨🌞
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+ [![Buy me a coffee](https://badgen.net/badge/icon/Buy%20Me%20A%20Coffee?icon=buymeacoffee&label)](https://bmc.link/edoardofederici)
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  <p align="center">
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  <img src="https://upload.wikimedia.org/wikipedia/commons/1/1a/Pieter_Bruegel_d._%C3%84._066.jpg" width="600"> </br>
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  Pieter Bruegel the Elder, The Fight Between Carnival and Lent, 1559