Update 07-run-model.md

Author: pareenaverma

content/learning-paths/mobile-graphics-and-gaming/measure-kleidiai-kernel-performance-on-executorch/07-run-model.md

@@ -20,16 +20,16 @@ The flags below tell executor_runner where to write the ETDump and how many time
 
 ```bash 
 cd ~/bench
-./executor_runner -etdump_path model/linear_model_f32.etdump -model_path model/linear_model_f32.pte -num_executions=1 -cpu_threads 1
+./executor_runner -etdump_path model/linear_model_pf32_gemm.etdump -model_path model/linear_model_pf32_gemm.pte -num_executions=1 -cpu_threads 1
 
 ```
 
 You can adjust the number of execution threads and the number of times the model is invoked.
 
 
-You should see output similar to the example below.
+You should see logs like:
 
-```bash
+```output
 D 00:00:00.015988 executorch:XNNPACKBackend.cpp:57] Creating XNN workspace
 D 00:00:00.018719 executorch:XNNPACKBackend.cpp:69] Created XNN workspace: 0xaff21c2323e0
 D 00:00:00.027595 executorch:operator_registry.cpp:96] Successfully registered all kernels from shared library: NOT_SUPPORTED
@@ -52,6 +52,6 @@ OutputX 0: tensor(sizes=[1, 256], [
 I 00:00:00.093912 executorch:executor_runner.cpp:125] ETDump written to file 'model/linear_model_f32.etdump'.
 
 ```
+If execution succeeds, an ETDump file is created next to your model. You will load the .etdump in the next section and analyze which operators dispatched to KleidiAI and how each micro-kernel performed.
 
-If the execution is successful, an etdump file will also be generated.