Update README.md

README.md

@@ -15,16 +15,6 @@ Inference of this model is compatible with AutoGPTQ's Kernel.
 
 
 
-### Evaluate the model 
-
-Install [lm-eval-harness](https://github.com/EleutherAI/lm-evaluation-harness.git) from source, we used the git id 96d185fa6232a5ab685ba7c43e45d1dbb3bb906d
-
-```bash
-lm_eval --model hf --model_args pretrained="Intel/gpt-neox-20b-int4-inc",autogptq=True,gptq_use_triton=True --device cuda:0 --tasks lambada_openai,hellaswag,piqa,winogrande,truthfulqa_mc1,openbookqa,boolq,rte,arc_easy,arc_challenge,mmlu --batch_size 32
-```
-
-
-
 ### Reproduce the model
 
 Here is the sample command to reproduce the model
@@ -49,6 +39,18 @@ python3 main.py \
 
 
 
+
+### Evaluate the model 
+
+Install [lm-eval-harness](https://github.com/EleutherAI/lm-evaluation-harness.git) from source, we used the git id 96d185fa6232a5ab685ba7c43e45d1dbb3bb906d
+
+```bash
+lm_eval --model hf --model_args pretrained="Intel/gpt-neox-20b-int4-inc",autogptq=True,gptq_use_triton=True --device cuda:0 --tasks lambada_openai,hellaswag,piqa,winogrande,truthfulqa_mc1,openbookqa,boolq,rte,arc_easy,arc_challenge,mmlu --batch_size 32
+```
+
+
+
+
 ## Caveats and Recommendations
 
 Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.