diff --git a/tutorials/llm/mamba/mamba.rst b/tutorials/llm/mamba/mamba.rst
index 525be296730a..2ce5ee5f616b 100644
--- a/tutorials/llm/mamba/mamba.rst
+++ b/tutorials/llm/mamba/mamba.rst
@@ -28,6 +28,7 @@ In order to proceed, ensure that you have met the following requirements:
 
 * A Docker-enabled environment, with `NVIDIA Container Runtime <https://developer.nvidia.com/container-runtime>`_ installed, which will make the container GPU-aware.
 
+
 * `Authenticate with NVIDIA NGC <https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html#ngc-authentication>`_, generate API KEY from `NGC <https://org.ngc.nvidia.com/setup >`__, add the key to your credentials following instructions in `this guide <https://docs.nvidia.com/launchpad/ai/base-command-coe/latest/bc-coe-docker-basics-step-02.html>`__, and get into NVIDIA NeMo dev container ``nvcr.io/nvidia/nemo:dev``.
 
 Step-by-step Guide for Fine-Tuning 
@@ -51,13 +52,13 @@ Convert the Pytorch Checkpoint to a NeMo Checkpoint
 
 .. code:: bash
 
-    CUDA_VISIBLE_DEVICES="0" python /NeMo/scripts/checkpoint_converters/convert_mamba2_pyt_to_nemo.py \
+    CUDA_VISIBLE_DEVICES="0" python /opt/NeMo/scripts/checkpoint_converters/convert_mamba2_pyt_to_nemo.py \
                                     --input_name_or_path <path to the source pytorch model> \
                                     --output_path <path to target .nemo model> \
-                                    --ngroups_mamba 8 \
+                                    --mamba_ssm_ngroups 8 \
                                     --precision bf16
 
-* Note: the ``ngroups_mamba`` parameter should be 1 for the Mamba2 models from the `Transformers are SSMs paper <https://arxiv.org/pdf/2405.21060>`__ (130m, 370m, 780m, 1.3b, and 2.7b) and 8 for the Mamba2 and Mamba2-Hybrid models by `NVIDIA <https://arxiv.org/pdf/2406.07887>`__ (both 8b).
+* Note: the ``mamba_ssm_ngroups`` parameter should be 1 for the Mamba2 models from the `Transformers are SSMs paper <https://arxiv.org/pdf/2405.21060>`__ (130m, 370m, 780m, 1.3b, and 2.7b) and 8 for the Mamba2 and Mamba2-Hybrid models by `NVIDIA <https://arxiv.org/pdf/2406.07887>`__ (both 8b).
 
 Model (Tensor) Parallelism for the 8b Models
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -106,8 +107,8 @@ Run Fine-Tuning
     export NVTE_FUSED_ATTN=1
     export NVTE_FLASH_ATTN=0
 
-    MASTER_PORT=15008 torchrun --nproc_per_node=${NUM_DEVICES} 
-            /home/ataghibakhsh/NeMo/examples/nlp/language_modeling/tuning/megatron_mamba_finetuning.py \
+    torchrun --nproc_per_node=${NUM_DEVICES} 
+            /opt/NeMo/examples/nlp/language_modeling/tuning/megatron_mamba_finetuning.py \
             --config-path=${CONFIG_PATH} \
             --config-name=${CONFIG_NAME} \
             trainer.devices=${NUM_DEVICES} \