Update README.md (#411)

README.md

@@ -88,6 +88,7 @@ following paths:
 
 1. Take a glance at the [Triton product page](https://developer.nvidia.com/nvidia-triton-inference-server) to get a sense of what Triton is used for.
 2. Download and run the [introductory example](https://github.com/triton-inference-server/fil_backend/tree/main/notebooks/categorical-fraud-detection) for yourself. If you do not have access to a GPU locally, you can just look over this notebook and then jump to the [FAQ notebook](https://github.com/triton-inference-server/fil_backend/tree/main/notebooks/faq) which has specific information on CPU-only training and deployment.
+
 **I have never worked with tree models before.**
 1. Take a look at XGBoost's [documentation](https://xgboost.readthedocs.io/en/stable/get_started.html#python).
 2. Download and run the [introductory example](https://github.com/triton-inference-server/fil_backend/tree/main/notebooks/categorical-fraud-detection) for yourself.