update notebook link

integration/nemo/examples/prompt_learning/prompt_learning.ipynb

@@ -14,7 +14,7 @@
     "The prompt learning technique shown in the example is [p-tuning](https://arxiv.org/abs/2103.10385), which adds a small prompt encoder network to the LLM\n",
     "to produce virtual token embeddings that guide the model toward the desired output of the downstream task.\n",
     "\n",
-    "For more details on how to change hyperparameters for prompt learning in NeMo, see this [tutorial](https://github.com/NVIDIA/NeMo/blob/main/tutorials/nlp/Multitask_Prompt_and_PTuning.ipynb) which is also the basis for this NVFlare tutorial.\n",
+    "For more details on how to change hyperparameters for prompt learning in NeMo, see this [tutorial](https://github.com/NVIDIA/NeMo/blob/v1.22.0/tutorials/nlp/Multitask_Prompt_and_PTuning.ipynb) which is also the basis for this NVFlare tutorial.\n",
     "\n",
     "<img src=\"./figs/p-tuning.svg\"  width=\"50%\" height=\"50%\">\n",
     "\n",

integration/nemo/examples/prompt_learning/prompt_learning_20B.md

@@ -7,7 +7,7 @@ a downstream task such as financial sentiment predictions.
 The prompt learning technique shown in the example is p-tuning which adds a small prompt encoder network to the LLM
 to produce virtual tokens that guide the model toward the desired output of the downstream task.
 
-For more details on how to change hyperparameters for prompt learning in NeMo, see this [tutorial](https://github.com/NVIDIA/NeMo/blob/main/tutorials/nlp/Multitask_Prompt_and_PTuning.ipynb) which is also the basis for this NVFlare tutorial.
+For more details on how to change hyperparameters for prompt learning in NeMo, see this [tutorial](https://github.com/NVIDIA/NeMo/blob/v1.22.0/tutorials/nlp/Multitask_Prompt_and_PTuning.ipynb) which is also the basis for this NVFlare tutorial.
 
 ## Dependencies
 This example running a 20B GPT model requires more computational resources.