Update README.md

README.md

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 ## Overview
 
-EuroBERT is a family of the most powerful multilingual encoder foundation models designed for a variety of tasks—such as classification, retrieval, or evaluation metrics—across 15 languages, including mathematics and code, and supports sequences of up to 8,192 tokens.
-
-EuroBERT incorporates recent architectural advances from decoder models (such as RoPE and Flash Attention) and is trained on a 5T-token multilingual dataset covering 8 European languages and 7 widely spoken global languages, along with mathematics and code. EuroBERT models exhibit the strongest multilingual performance across domains and tasks compared to similarly sized systems.
+EuroBERT is a family of multilingual encoder models designed for a variety of tasks—such as classification, retrieval, or evaluation metrics— supporting 15 languages, mathematics and code, and sequences of up to 8,192 tokens.
+EuroBERT models exhibit the strongest multilingual performance across [domains and tasks](#Evaluation) compared to similarly sized systems.
 
 It is available in the following sizes:
 
@@ -46,7 +45,7 @@ It is available in the following sizes:
 - [EuroBERT-610m](https://huggingface.co/EuroBERT/EuroBERT-610m) - 26 layers, 610 million parameters
 - [EuroBERT-2.1B](https://huggingface.co/EuroBERT/EuroBERT-2.1B) - 32 layers, 2.1 billion parameters
 
-For more information about EuroBERT, please refer to the [release blog post](https://huggingface.co/blog/modernbert) for a high-level overview and our [arXiv pre-print](https://arxiv.org/abs/2412.13663) for in-depth information.
+For more information about EuroBERT, please refer to the [release blog post](***) for a high-level overview and our [arXiv pre-print](***) for in-depth information.
 
 ## Usage