Update index.html

index.html

@@ -137,7 +137,7 @@
             To achieve this, we develop a principled data curation strategy that augments public datasets with synthetically generated critiques and ensures high quality through filtering and dataset ablations. We train our model on a combined direct preference optimization (DPO) and supervised fine-tuning (SFT) loss, and produce a highly promptable evaluator that excels in real-world scenarios.
           </p>
           <p>
-            Selene Mini shows dramatically improved zero-shot agreement with human expert evaluations on financial and medical industry datasets. It is also robust to variations in prompt format. Preliminary results indicate that Selene Mini is the top-ranking evaluator in a live, community-driven Judge Arena. We release the model weights on HuggingFace and Ollama to encourage widespread community adoption.
+            Selene Mini shows dramatically improved zero-shot agreement with human expert evaluations on financial and medical industry datasets. It is also robust to variations in prompt format. Preliminary results indicate that Selene Mini is the top-ranking evaluator in a live, community-driven <a href="https://huggingface.co/blog/arena-atla" target="_blank">Judge Arena</a>. We release the model weights on <a href="https://hf.co/AtlaAI/Selene-1-Mini-Llama-3.1-8B" target="_blank">HuggingFace</a> and <a href="https://ollama.com/atla/selene-mini" target="_blank">Ollama</a> to encourage widespread community adoption.
           </p>
         </div>
       </div>