Update README.md

README.md

@@ -252,6 +252,8 @@ This model also features Grouped Attention Query (GQA) so that memory usage scal
 
 Instruction fine tuning was performed with a combination of supervised fine-tuning (SFT), rejection sampling, proximal policy optimization (PPO), and direct policy optimization (DPO).
 
+Check out their blog post for more information [here](https://ai.meta.com/blog/meta-llama-3/)
+
 ## Special thanks
 
 🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.