diff --git a/onnx-benchmark/README.md b/onnx-benchmark/README.md
index c9c9feff..86953d82 100644
--- a/onnx-benchmark/README.md
+++ b/onnx-benchmark/README.md
@@ -35,11 +35,7 @@ Author: AMD-Xilinx
     - [3.3.8 File of parameters](#338-file-of-parameters)
 - [4 Additional features](#4-additional-features)
   - [4.1 Auto quantization](#41-auto-quantization)
-<<<<<<< HEAD
   - [4.2 Tricks](#42-tricks)
-=======
-  - [4.2 tricks](#42-tricks)
->>>>>>> b02f64fa (Merge branch 'VitisAI:main' into main_ci_add)
 
 
 # <a name='Title'></a>RYZENAI-ONNX-CNNs-BENCHMARK
@@ -83,7 +79,6 @@ conda env config vars set VAIP_CONFIG_HOME="C:\Program Files\RyzenAI\1.2.0\voe-4
 conda deactivate
 conda activate ryzen-ai-1.2.0
 conda env config vars list
-<<<<<<< HEAD
 ```
 
 In case of PHOENIX device:
@@ -101,8 +96,6 @@ Downgrade onnx to 1.16.1 to resolve an issue with the 1.16.2 release
 https://github.com/onnx/onnx/issues/6267 
 ```
 pip install onnx==1.16.1
-=======
->>>>>>> b02f64fa (Merge branch 'VitisAI:main' into main_ci_add)
 ```
 
 In case of PHOENIX device:
@@ -116,6 +109,13 @@ conda activate ryzen-ai-1.2.0
 conda env config vars list
 ```
 
+Downgrade onnx to 1.16.1 to resolve an issue with the 1.16.2 release
+https://github.com/onnx/onnx/issues/6267 
+```
+pip install onnx==1.16.1
+```
+
+
 ---
 
 #  3 <a name='ONNXBenchmark'></a>ONNX Benchmark
@@ -269,9 +269,5 @@ Prior to quantization, the user is required to download some images, for example
 python performance_benchmark.py -m ".\models\resnet50\resnet50_fp32.onnx" -e VitisAIEP --calib <images folder> --num_calib 10
 ```
 
-<<<<<<< HEAD
 ## 4.2 Tricks
-=======
-## 4.2 tricks
->>>>>>> b02f64fa (Merge branch 'VitisAI:main' into main_ci_add)
 Once executed in the GUI, the equivalent command line is copied to the clipboard, making it easy to paste into the terminal.
diff --git a/onnx-benchmark/utilities.py b/onnx-benchmark/utilities.py
index e40d08f7..ee8cb67a 100644
--- a/onnx-benchmark/utilities.py
+++ b/onnx-benchmark/utilities.py
@@ -469,28 +469,8 @@ def ggquantize(args):
     newopset = 17
     original_model = onnx.load(input_model_path)
     opset_version = original_model.opset_import[0].version
-<<<<<<< HEAD
 
     # temporary fix: after conversion the opset is not updated to 17 but to 1
-    if opset_version<11:
-        if opset_version==1 :
-            ggprint(f'[WARNING] The model opset version is 1, which seems unlikely. This might be the result of a previous opset conversion.')
-        else:
-            ggprint(f'The model OPSET is {opset_version} and should be updated to {newopset}')
-            user_response = ask_update()
-            if user_response == 'y':
-                output_updated = f"{base_name}_opset17{extension}"
-                converted_model = version_converter.convert_version(original_model, newopset)
-                #print(f"The model after conversion:\n{converted_model}")
-                onnx.save(converted_model, output_updated)
-                print(f'The update model was saved with name {output_updated}')
-                # verify opset
-                updated_model = onnx.load(output_updated)
-                ggprint(f"Updated model opset version: {updated_model.opset_import[0].version}")
-                input_model_path = output_updated
-            else:
-                ggprint("You chose not to update")
-=======
     if opset_version<11:
         ggprint(f'The model OPSET is {opset_version} and should be updated to {newopset}')
         user_response = ask_update()
@@ -503,7 +483,6 @@ def ggquantize(args):
             input_model_path = output_updated
         else:
             print("You chose not to update")
->>>>>>> b02f64fa (Merge branch 'VitisAI:main' into main_ci_add)
     # free memory
     del original_model
     gc.collect()