diff --git a/CHANGELOGS.rst b/CHANGELOGS.rst
index fc5852ed..0f9b7f7d 100644
--- a/CHANGELOGS.rst
+++ b/CHANGELOGS.rst
@@ -4,6 +4,7 @@ Change Logs
 0.7.14
 ++++++
 
+* :pr:`252`: adds new set of inputs for task texgt-generation
 * :pr:`250`: add variables to track sequence nodes
 * :pr:`249`: patches _maybe_broadcast to support a corner case
 
diff --git a/onnx_diagnostic/_command_lines_parser.py b/onnx_diagnostic/_command_lines_parser.py
index 2c6f72b1..8632d34f 100644
--- a/onnx_diagnostic/_command_lines_parser.py
+++ b/onnx_diagnostic/_command_lines_parser.py
@@ -400,12 +400,17 @@ def get_parser_validate() -> ArgumentParser:
 
             position_ids is usually not needed, they can be removed by adding:
 
-            --drop position_ids
+                --drop position_ids
 
             The behaviour may be modified compare the original configuration,
             the following argument can be rope_scaling to dynamic:
 
-            --mop \"rope_scaling={'rope_type': 'dynamic', 'factor': 10.0}\""
+                --mop \"rope_scaling={'rope_type': 'dynamic', 'factor': 10.0}\""
+
+            You can profile the command line by running:
+
+                pyinstrument -m onnx_diagnostic validate ...
+                pyinstrument -r html -o profile.html -m onnx_diagnostic validate ...
             """
         ),
         formatter_class=RawTextHelpFormatter,
diff --git a/onnx_diagnostic/torch_models/validate.py b/onnx_diagnostic/torch_models/validate.py
index 9bccf9f1..e90c3420 100644
--- a/onnx_diagnostic/torch_models/validate.py
+++ b/onnx_diagnostic/torch_models/validate.py
@@ -419,14 +419,14 @@ def validate_model(
         such as ``input_empty_cache``
         which refers to a set of inputs using an empty cache.
     """
-    validation_begin = time.perf_counter()
+    main_validation_begin = time.perf_counter()
     model_id, subfolder, same_as_pretrained, use_pretrained = _preprocess_model_id(
         model_id,
         subfolder,
         same_as_pretrained=same_as_pretrained,
         use_pretrained=use_pretrained,
     )
-    time_preprocess_model_id = time.perf_counter() - validation_begin
+    time_preprocess_model_id = time.perf_counter() - main_validation_begin
     default_patch = dict(patch_transformers=True, patch_diffusers=True, patch=True)
     if isinstance(patch, bool):
         patch_kwargs = default_patch if patch else dict(patch=False)
@@ -921,7 +921,7 @@ def validate_model(
                 summary.update(summary_valid)
 
     _compute_final_statistics(summary)
-    summary["time_total"] = time.perf_counter() - validation_begin
+    summary["time_total"] = time.perf_counter() - main_validation_begin
 
     if verbose:
         print("[validate_model] -- done (final)")