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@@ -469,7 +469,7 @@ <h2 class="title is-3">Method</h2>
           <p>
             We collect <a href="https://huggingface.co/datasets/HaoyeZhang/RLHF-V-Hall_v0/tree/main">1.4k fine-grained dense feedback data</a> by asking human annotators to correct the hallucinated segments in model responses.
 
-            For training, it takes only 1 hour with 8 A100 GPUs to get <a href="https://huggingface.co/openbmb/RLHF-V_v0">RLHF-V-13B</a> which is initialized from our <a href="https://huggingface.co/Yirany/RLHF-V_v0_SFT/tree/main">RLHF-V_SFT-13B</a>.
+            The training takes only 1 hour with 8 A100 GPUs to get <a href="https://huggingface.co/openbmb/RLHF-V_v0">RLHF-V-13B</a> which is initialized from our <a href="https://huggingface.co/Yirany/RLHF-V_v0_SFT/tree/main">RLHF-V_SFT-13B</a>.
           </p>
           <ul>
             <!-- <li>It has two types of queries (latent queries and text queries) and outputs (semantic outputs and pixel-level outputs).</li>