diff --git a/docs/examples/te_llama/requirements.txt b/docs/examples/te_llama/requirements.txt
new file mode 100644
index 0000000000..093849001b
--- /dev/null
+++ b/docs/examples/te_llama/requirements.txt
@@ -0,0 +1,5 @@
+transformers==4.57.0
+accelerate==1.10.0
+peft==0.15.2
+datasets==4.0.0
+sentencepiece==0.2.1
diff --git a/docs/examples/te_llama/te_llama.py b/docs/examples/te_llama/te_llama.py
index b2d4d183ab..6dfa9b67bb 100644
--- a/docs/examples/te_llama/te_llama.py
+++ b/docs/examples/te_llama/te_llama.py
@@ -72,10 +72,15 @@ def forward(self, hidden_states, *args, attention_mask, **kwargs):
         forward pass of the `TransformerLayer`. Also, make sure the output
         format matches the output of the HF's `LlamaDecoderLayer`.
         """
-        return (
-            super().forward(
-                hidden_states, attention_mask=attention_mask, rotary_pos_emb=self.te_rope_emb
-            ),
+        # Handle case where hidden_states might be a tuple (from previous layer output)
+        # This can happen with older versions of HuggingFace transformers
+        if isinstance(hidden_states, tuple):
+            hidden_states = hidden_states[0]
+
+        # Return tensor directly for HuggingFace transformers >= 4.57
+        # (older versions wrapped output in tuple and extracted with layer_outputs[0])
+        return super().forward(
+            hidden_states, attention_mask=attention_mask, rotary_pos_emb=self.te_rope_emb
         )
 
 
@@ -162,7 +167,7 @@ def replace_params(hf_state_dict, te_state_dict, config):
     # collect all layer prefixes to update
     all_layer_prefixes = set()
     for param_key in hf_state_dict.keys():
-        layer_prefix_pat = "model.layers.\d+."
+        layer_prefix_pat = r"model.layers.\d+."
         m = re.match(layer_prefix_pat, param_key)
         if m is not None:
             all_layer_prefixes.add(m.group())
diff --git a/docs/examples/te_llama/tutorial_accelerate_hf_llama_with_te.ipynb b/docs/examples/te_llama/tutorial_accelerate_hf_llama_with_te.ipynb
index 00499cff5f..42eee386b9 100644
--- a/docs/examples/te_llama/tutorial_accelerate_hf_llama_with_te.ipynb
+++ b/docs/examples/te_llama/tutorial_accelerate_hf_llama_with_te.ipynb
@@ -29,12 +29,11 @@
     "    - This file contains the code to load a Hugging Face Llama 2 or Llama 3 checkpoint in Transformer Engine's `TransformerLayer` instead of Hugging Face's `LlamaDecoderLayer`. This is used in the following two sections of the tutorial - \"Improvement 1\" and \"Improvement 2\".\n",
     "2. `utils.py`\n",
     "    - This file contains the code related to dataloading, hyperparameters, setting up model/optimizers/accelerator, model training and other miscellaneous tasks like restarting the jupyter notebook from within the cell. \n",
-    "3. `media/`\n",
+    "3. `requirements.txt`\n",
+    "    - This file contains the necessary Python packages for this tutorial.\n",
+    "4. `media/`\n",
     "    - This directory contains the images used in the following tutorial.\n",
     "\n",
-    "These packages are necessary to run this tutorial:\n",
-    "`pytorch`, `transformer_engine`, `accelerate`, `transformers`, `peft`, `datasets`.\n",
-    "\n",
     "\n",
     "<div class=\"alert alert-info\">\n",
     "\n",
@@ -45,6 +44,27 @@
     "</div>\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "b56526b3",
+   "metadata": {},
+   "source": [
+    "### Setup\n",
+    "\n",
+    "Install the required Python packages using the following command:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "099697e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Uncomment and run this cell when running the tutorial for the first time\n",
+    "# %pip install -r requirements.txt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "44abae4f",
@@ -233,12 +253,12 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
      "output_type": "stream",
      "text": [
       "10 finetuning steps complete!\n",
       "Average time taken per step: 248 milliseconds\n"
-     ]
+     ],
+     "name": "stdout"
     }
    ],
    "source": [
@@ -568,12 +588,12 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
      "output_type": "stream",
      "text": [
       "10 finetuning steps complete!\n",
       "Average time taken per step: 185 milliseconds\n"
-     ]
+     ],
+     "name": "stdout"
     }
    ],
    "source": [
@@ -657,12 +677,12 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
      "output_type": "stream",
      "text": [
       "10 finetuning steps complete!\n",
       "Average time taken per step: 160 milliseconds\n"
-     ]
+     ],
+     "name": "stdout"
     }
    ],
    "source": [
@@ -755,9 +775,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.13.3"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}
\ No newline at end of file