Update README.md

README.md

@@ -25,7 +25,7 @@ language:
 - **Model Developers:** Neural Magic
 
 Quantized version of [Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct).
-It achieves an average score of 82.00 on the [OpenLLM](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) benchmark (version 1), whereas the unquantized model achieves 82.74.
+It achieves an average score of 83.14 on the [OpenLLM](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) benchmark (version 1), whereas the unquantized model achieves 83.61.
 
 ### Model Optimizations
 
@@ -163,7 +163,7 @@ oneshot(
 ## Evaluation
 
 The model was evaluated on the [OpenLLM](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) leaderboard tasks (version 1) with the [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) and the [vLLM](https://docs.vllm.ai/en/stable/) engine, using the following command.
-A modified version of ARC-C was used for evaluations, in line with Llama 3.1's prompting.
+A modified version of ARC-C and GSM8k-cot was used for evaluations, in line with Llama 3.1's prompting. It can be accessed on the [Neural Magic fork of the lm-evaluation-harness](https://github.com/neuralmagic/lm-evaluation-harness/tree/llama_3.1_instruct).
 ```
 lm_eval \
   --model vllm \
@@ -197,7 +197,7 @@ lm_eval \
    </td>
   </tr>
   <tr>
-   <td>ARC Challenge (25-shot)
+   <td>ARC Challenge (0-shot)
    </td>
    <td>95.05
    </td>
@@ -207,13 +207,13 @@ lm_eval \
    </td>
   </tr>
   <tr>
-   <td>GSM-8K (5-shot, strict-match)
+   <td>GSM-8K-cot (8-shot, strict-match)
    </td>
-   <td>87.95
+   <td>93.18
    </td>
-   <td>86.50
+   <td>93.33
    </td>
-   <td>98.35%
+   <td>100.1%
    </td>
   </tr>
   <tr>
@@ -249,11 +249,11 @@ lm_eval \
   <tr>
    <td><strong>Average</strong>
    </td>
-   <td><strong>82.74</strong>
+   <td><strong>83.61</strong>
    </td>
-   <td><strong>82.00</strong>
+   <td><strong>83.14</strong>
    </td>
-   <td><strong>99.10%</strong>
+   <td><strong>99.43%</strong>
    </td>
   </tr>
 </table>