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@@ -19,16 +19,24 @@ inference: false
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  <p align="center" style="margin:0;padding:0">
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- <img src="https://huggingface.co/BramVanroy/fietje-2b/resolve/main/img/fietje-2b-banner.png" alt="Fietje banner" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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  </p>
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  <div style="margin:auto; text-align:center">
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- <h1 style="margin-bottom: 0">Fietje 2B</h1>
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- <em>An open and efficient LLM for Dutch.</em>
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  </div>
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- > [!TIP]
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- > πŸš€ Looking for the fast GGUF version? You can find it, and how to use it with `ollama` (command line) or LM Studio (interface), [here](https://huggingface.co/BramVanroy/fietje-2b-GGUF).
 
 
 
 
 
 
 
 
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  This model is an adapted version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2), finetuned for Dutch text generation. It was continue-pretrained on 28B Dutch tokens, which includes the full Dutch component of Wikipedia (accounting for around 15%), supplemented with Dutch tokens from CulturaX. A newer version of this dataset can be found [here](https://huggingface.co/datasets/BramVanroy/wikipedia_culturax_dutch), which also describes the filtering that took place.
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  <p align="center" style="margin:0;padding:0">
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+ <img src="https://huggingface.co/BramVanroy/fietje-2b/resolve/main/img/fietje-2b-banner.png" alt="Fietje banner" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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  </p>
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  <div style="margin:auto; text-align:center">
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+ <h1 style="margin-bottom: 0">Fietje 2B</h1>
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+ <em>An open and efficient LLM for Dutch.</em>
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  </div>
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+ <blockquote class="tip">
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+ <p align="center">
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+ <a rel="nofollow" href="https://huggingface.co/BramVanroy/fietje-2b">πŸ‘±β€β™€οΈ Base version</a> (this one) -
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+ <a rel="nofollow" href="https://huggingface.co/BramVanroy/fietje-2b-instruct">πŸ€– Instruct version</a> -
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+ <a rel="nofollow" href="https://huggingface.co/BramVanroy/fietje-2b-chat">πŸ’¬ Chat version</a> -
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+ <a rel="nofollow" href="https://huggingface.co/BramVanroy/fietje-2b-GGUF">πŸš€ GGUF of base model</a>
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+ </p>
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+ </blockquote>
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  This model is an adapted version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2), finetuned for Dutch text generation. It was continue-pretrained on 28B Dutch tokens, which includes the full Dutch component of Wikipedia (accounting for around 15%), supplemented with Dutch tokens from CulturaX. A newer version of this dataset can be found [here](https://huggingface.co/datasets/BramVanroy/wikipedia_culturax_dutch), which also describes the filtering that took place.
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