Update README.md

README.md

@@ -114,32 +114,10 @@ mera-mix-4x7B achieves the score of 75.91 on the OpenLLM Eval and compares well
 
 You can try the model with the [Mera Mixture Chat](https://huggingface.co/spaces/meraGPT/mera-mixture-chat).
 
-<!--
-## OpenLLM Eval
-
-|                            Model                            | ARC |HellaSwag|MMLU |TruthfulQA|Winogrande|GSM8K|Average|
-|-------------------------------------------------------------|----:|--------:|----:|---------:|---------:|----:|------:|
-|[mera-mix-4x7B](https://huggingface.co/meraGPT/mera-mix-4x7B)|72.01|    88.82|63.67|     77.45|     84.61|71.65|  76.37|
-
-Raw eval results are available at this [gist](https://gist.github.com/codelion/78f88333230801c9bbaa6fc22078d820)
--->
-
-# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
-Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_meraGPT__mera-mix-4x7B)
-
-|             Metric              |Value|
-|---------------------------------|----:|
-|Avg.                             |75.91|
-|AI2 Reasoning Challenge (25-Shot)|72.95|
-|HellaSwag (10-Shot)              |89.17|
-|MMLU (5-Shot)                    |64.44|
-|TruthfulQA (0-shot)              |77.17|
-|Winogrande (5-shot)              |85.64|
-|GSM8k (5-shot)                   |66.11|
-
 In addition, to the official Open LLM Leaderboard, the results on OpenLLM Eval have been validated by [others as well (76.59)](https://github.com/saucam/model_evals/tree/main?tab=readme-ov-file#model-eval-results).
 
 Our own initial eval is available [here (76.37)](https://gist.github.com/codelion/78f88333230801c9bbaa6fc22078d820). 
+
 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
 Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_meraGPT__mera-mix-4x7B)