Update deploy-models-llama.md

Author: ssalgadodev

articles/ai-studio/how-to/deploy-models-llama.md

@@ -537,15 +537,26 @@ For reference about how to invoke Llama models deployed to managed compute, see
 
 ##### More inference examples
 
+# [Meta Llama 3](#tab/llama-three)
+
 | **Package**       | **Sample Notebook**                             |
 |----------------|----------------------------------------|
-| CLI using CURL and Python web requests - Command R   | [command-r.ipynb](https://aka.ms/samples/cohere-command-r/webrequests)|
-| CLI using CURL and Python web requests - Command R+   | [command-r-plus.ipynb](https://aka.ms/samples/cohere-command-r-plus/webrequests)|
 | OpenAI SDK (experimental)    | [openaisdk.ipynb](https://aka.ms/samples/meta-llama3/openaisdk)                                    |
 | LangChain      | [langchain.ipynb](https://aka.ms/samples/meta-llama3/langchain)                                |
 | WebRequests     | [webrequests.ipynb]((https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/meta-llama3/webrequests.ipynb))                                 |
 | LiteLLM SDK    | [litellm.ipynb](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/meta-llama3/litellm.ipynb) |
 
+# [Meta Llama 2](#tab/llama-two)
+
+| **Package**       | **Sample Notebook**                             |
+|----------------|----------------------------------------|
+| OpenAI SDK (experimental)    | [openaisdk.ipynb](https://aka.ms/samples/llama2/openaisdk)                                    |
+| LangChain      | [langchain.ipynb](https://aka.ms/samples/llama2/langchain)                                |
+| WebRequests     | [webrequests.ipynb]((https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/llama2/webrequests.ipynb))                                 |
+| LiteLLM SDK    | [litellm.ipynb](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/llama2/litellm.ipynb) |
+
+---
+
 ## Cost and quotas
 
 ### Cost and quota considerations for Llama models deployed as a service