nerdy-tech-com-gitub
diff --git a/‎recipes/llama_api_providers/examples_with_aws/ReAct_Llama_2_Bedrock-WK.ipynb renamed to ‎recipes/llama_api_providers/examples_with_aws/ReAct_Llama_Bedrock-WK.ipynb b/‎recipes/llama_api_providers/examples_with_aws/ReAct_Llama_2_Bedrock-WK.ipynb renamed to ‎recipes/llama_api_providers/examples_with_aws/ReAct_Llama_Bedrock-WK.ipynb
diff --git a/‎recipes/llama_api_providers/examples_with_aws/getting_started_llama2_on_amazon_bedrock.ipynb renamed to ‎recipes/llama_api_providers/examples_with_aws/getting_started_llama_on_amazon_bedrock.ipynb b/‎recipes/llama_api_providers/examples_with_aws/getting_started_llama2_on_amazon_bedrock.ipynb renamed to ‎recipes/llama_api_providers/examples_with_aws/getting_started_llama_on_amazon_bedrock.ipynb
diff --git a/‎recipes/quickstart/Prompt_Engineering_with_Llama_2.ipynb
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@@ -7,6 +7,9 @@
    "source": [
     "# Prompt Engineering with Llama 2 - Using Amazon Bedrock + LangChain\n",
     "\n",
+    "Open this notebook in <a href=\"https://colab.research.google.com/github/meta-llama/llama-recipes/blob/main/recipes/quickstart/Prompt_Engineering_with_Llama_2.ipynb\"><img data-canonical-src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\" src=\"https://camo.githubusercontent.com/f5e0d0538a9c2972b5d413e0ace04cecd8efd828d133133933dfffec282a4e1b/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667\"></a>\n",
+    "\n",
+    "\n",
     "Prompt engineering is using natural language to produce a desired response from a large language model (LLM).\n",
     "\n",
     "This interactive guide covers prompt engineering & best practices with Llama 2.\n",