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getting-started/README.md

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 If you are new to developing with Meta Llama models, this is where you should start. This folder contains introductory-level notebooks across different techniques relating to Meta Llama.
 
 * The [Build_with_Llama 4](./build_with_llama_4.ipynb) notebook showcases a comprehensive walkthrough of the new capabilities of Llama 4 Scout models, including long context, multi-images and function calling.
+* The [Build_with_Llama API](./build_with_llama_api.ipynb) notebook highlights some of the features of [Llama API](https://llama.developer.meta.com).
 * The [inference](./inference/) folder contains scripts to deploy Llama for inference on server and mobile. See also [3p_integrations/vllm](../3p-integrations/vllm/) and [3p_integrations/tgi](../3p-integrations/tgi/) for hosting Llama on open-source model servers.
 * The [RAG](./RAG/) folder contains a simple Retrieval-Augmented Generation application using Llama.
 * The [finetuning](./finetuning/) folder contains resources to help you finetune Llama on your custom datasets, for both single- and multi-GPU setups. The scripts use the native llama-cookbook finetuning code found in [finetuning.py](../src/llama_cookbook/finetuning.py) which supports these features: