[ez] point to stable llama3 tutorial link from readme (#815)

Author: ebsmothers

README.md

@@ -86,7 +86,7 @@ This table captures the minimum memory requirements for our different recipes us
 
 ## Llama3
 
-torchtune supports fine-tuning for the Llama3 8B models with support for 70B on its way. We currently support LoRA, QLoRA and Full-finetune on a single GPU as well as LoRA and Full fine-tune on multiple devices. For all the details, take a look at our [tutorial](https://pytorch.org/torchtune/main/tutorials/llama3.html).
+torchtune supports fine-tuning for the Llama3 8B models with support for 70B on its way. We currently support LoRA, QLoRA and Full-finetune on a single GPU as well as LoRA and Full fine-tune on multiple devices. For all the details, take a look at our [tutorial](https://pytorch.org/torchtune/stable/tutorials/llama3.html).
 
 
 In our initial experiments, QLoRA has a peak allocated memory of ``~9GB`` while LoRA on a single GPU has a peak allocated memory of ``~19GB``. To get started, you can use our default configs to kick off training.