Update README.md

README.md

@@ -3,23 +3,34 @@ license: mit
 base_model: microsoft/phi-2
 tags:
 - trl
-- sft
-- generated_from_trainer
+- conversational
+- fietje
+- alignment-handbook
 datasets:
-- arrow
+- uonlp/CulturaX
+- wikimedia/wikipedia
 model-index:
 - name: fietje-2b
   results: []
+language:
+- nl
+pipeline_tag: text-generation
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
 
-# fietje-2b
+<p align="center" style="margin:0;padding:0">
+<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'"/>
+</p>
 
-This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the arrow dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.4013
+<div style="margin:auto; text-align:center">
+<h1 style="margin-bottom: 0">Fietje 2B</h1>
+<em>An open and efficient LLM for Dutch.</em>
+</div>
+
+> [!TIP]
+> 🚀 Looking for the fast GGUF version? You can find it, and how to use it with `ollama`, [here](https://huggingface.co/BramVanroy/fietje-2b-GGUF). 🚀 
+
+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 and 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 A newer version of this dataset can be found [here](https://huggingface.co/datasets/BramVanroy/wikipedia_culturax_dutch), which also describes the filtering that took place.
 
 ## Model description
 
@@ -69,4 +80,4 @@ The following hyperparameters were used during training:
 - Transformers 4.39.1
 - Pytorch 2.1.2+cu121
 - Datasets 2.18.0
-- Tokenizers 0.15.2
+- Tokenizers 0.15.2