Update README.md

README.md

@@ -147,7 +147,7 @@ The model generated a single answer for each prompt form Arena-Hard, and each an
 We report below the scores obtained in each judgement and the average.
 
 OpenLLM v1 and v2 evaluations were conducted using Neural Magic's fork of [lm-evaluation-harness](https://github.com/neuralmagic/lm-evaluation-harness/tree/llama_3.1_instruct) (branch llama_3.1_instruct).
-This version of the lm-evaluation-harness includes versions of MMLU, ARC-Challenge and GSM-8K that match the prompting style of [Meta-Llama-3.1-Instruct-evals](https://huggingface.co/datasets/meta-llama/Meta-Llama-3.1-70B-Instruct-evals) and a few fixes to OpenLLM v2 tasks.
+This version of the lm-evaluation-harness includes versions of MMLU, ARC-Challenge and GSM-8K that match the prompting style of [Meta-Llama-3.1-Instruct-evals](https://huggingface.co/datasets/meta-llama/Meta-Llama-3.1-405B-Instruct-evals) and a few fixes to OpenLLM v2 tasks.
 
 HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of the [EvalPlus](https://github.com/neuralmagic/evalplus) repository.
 
@@ -155,7 +155,6 @@ Detailed model outputs are available as HuggingFace datasets for [Arena-Hard](ht
 
 ### Accuracy
 
-#### Open LLM Leaderboard evaluation scores
 <table>
   <tr>
    <td><strong>Benchmark</strong>