Update NeMo Curator notebook link

README.md

@@ -73,7 +73,7 @@ Success is defined as having an acceptable catch rate (recall scores for each at
 
 ## How to Use in NeMo Curator:
 The inference code is available on [NeMo Curator's GitHub repository](https://github.com/NVIDIA/NeMo-Curator). <br>
-Check out [this example notebook](https://github.com/NVIDIA/NeMo-Curator/tree/main/tutorials/distributed_data_classification) to get started.
+Check out [this example notebook](https://github.com/NVIDIA/NeMo-Curator/blob/main/tutorials/distributed_data_classification/instruction-data-guard-classification.ipynb) to get started.
 
 ## How to Use in Transformers:
 To use this AEGIS classifiers, you must get access to Llama Guard on Hugging Face here: https://huggingface.co/meta-llama/LlamaGuard-7b. Afterwards, you should set up a [user access token](https://huggingface.co/docs/hub/en/security-tokens) and pass that token into the constructor of this classifier.