diff --git a/README.md b/README.md
index 9851ced55..0d4e2939f 100644
--- a/README.md
+++ b/README.md
@@ -679,7 +679,9 @@ We support profiling with Nsight Systems, the PyTorch Profiler, and PyTorch Memo
 
 ## Nsight Systems Profiling
 
-To use the Nsight Systems profiling, set config options `profile`, `profile_step_start`, and `profile_step_stop`. Launch training with:
+To use the Nsight Systems profiling, set config options `profile`, `profile_step_start`, and `profile_step_stop` (see [here](https://github.com/EleutherAI/gpt-neox/blob/main/configs/neox_arguments.md) for argument usage, and [here](https://github.com/EleutherAI/gpt-neox/blob/main/configs/prof.yml) for a sample config).
+
+To populate nsys metrics, launch training with:
 
 ```
 nsys profile -s none -t nvtx,cuda -o <path/to/profiling/output> --force-overwrite true \
@@ -689,22 +691,22 @@ $TRAIN_PATH/train.py --conf_dir configs <config files>
 
 The generated output file can then by viewed with the Nsight Systems GUI:
 
-![Alt text](images/nsight_profiling.png)
+![nsight-prof](images/nsight_profiling.png)
 
 ## PyTorch Profiling
 
-To use the built-in PyTorch profiler, set config options `profile`, `profile_step_start`, and `profile_step_stop`.
+To use the built-in PyTorch profiler, set config options `profile`, `profile_step_start`, and `profile_step_stop` (see [here](https://github.com/EleutherAI/gpt-neox/blob/main/configs/neox_arguments.md) for argument usage, and [here](https://github.com/EleutherAI/gpt-neox/blob/main/configs/prof.yml) for a sample config).
 
 The PyTorch profiler will save traces to your `tensorboard` log directory.  You can view these traces within
 TensorBoard by following the steps [here](https://pytorch.org/tutorials/intermediate/tensorboard_profiler_tutorial.html).
 
-![Alt text](images/pytorch_profiling.png)
+![torch-prof](images/pytorch_profiling.png)
 
 ## PyTorch Memory Profiling
 
-To use PyTorch Memory Profiling, set config options `memory_profiling` and `memory_profiling_path`.
+To use PyTorch Memory Profiling, set config options `memory_profiling` and `memory_profiling_path` (see [here](https://github.com/EleutherAI/gpt-neox/blob/main/configs/neox_arguments.md) for argument usage, and [here](https://github.com/EleutherAI/gpt-neox/blob/main/configs/prof.yml) for a sample config).
 
-![Alt text](images/memory_profiling.png)
+![mem-prof](images/memory_profiling.png)
 
 View the generated profile with the [memory_viz.py](https://github.com/pytorch/pytorch/blob/main/torch/cuda/_memory_viz.py) script. Run with:
 
diff --git a/configs/prof.yml b/configs/prof.yml
new file mode 100644
index 000000000..c2f2ee118
--- /dev/null
+++ b/configs/prof.yml
@@ -0,0 +1,17 @@
+# Sample profiling config
+{
+  # Turns on nsys and pytorch profiling
+  "profile": true,
+
+  # pytorch profiler options
+  "profile_step_start": 10,
+  "profile_step_stop": 12,
+
+  # pytorch memory profiler options
+  "memory_profiling": true,
+  "memory_profiling_path": tensorboard,
+
+
+  # All trace files (pytorch, nsys, tensorboard, etc) will be written here
+  "tensorboard_dir": "tensorboard",
+}
diff --git a/megatron/neox_arguments/neox_args.py b/megatron/neox_arguments/neox_args.py
index b5dad71f5..ac313a3bb 100644
--- a/megatron/neox_arguments/neox_args.py
+++ b/megatron/neox_arguments/neox_args.py
@@ -732,8 +732,8 @@ class NeoXArgsLogging(NeoXArgsTemplate):
 
     profile: bool = False
     """
-    Enable nsys profiling. When using this option,
-    nsys options should be specified in commandline.
+    Enable nsys and pytorch profiling. When using this option with nsys,
+    nsys options should be directly specified in commandline.
     An example nsys commandline is
     ```
     nsys profile -s none -t nvtx,cuda -o <path/to/output_file>