update readme

README.md

@@ -19,7 +19,7 @@ We train the models on cloud TPU-v4s using [EasyLM](https://github.com/young-gen
 
 We evaluated OpenLLaMA on a wide range of tasks using [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness).  The LLaMA results are generated by running the original LLaMA model on the same evaluation metrics. We note that our results for the LLaMA model differ slightly from the original LLaMA paper, which we believe is a result of different evaluation protocols. Similar differences have been reported in [this issue of lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness/issues/443). Additionally, we present the results of GPT-J, a 6B parameter model trained on the [Pile](https://pile.eleuther.ai/) dataset by [EleutherAI](https://www.eleuther.ai/).
 
-The original LLaMA model was trained for 1 trillion tokens and GPT-J was trained for 500 million tokens, whereas OpenLLaMA was trained on 200 million tokens.  We present the results in the table below. OpenLLaMA exhibits comparable performance to the original LLaMA and GPT-J across a majority of tasks, and outperforms them in some tasks. We expect that the performance of OpenLLaMA, after completing its training on 1 trillion tokens, will be enhanced even further.
+The original LLaMA model was trained for 1 trillion tokens and GPT-J was trained for 500 billion tokens, whereas OpenLLaMA was trained on 200 billion tokens.  We present the results in the table below. OpenLLaMA exhibits comparable performance to the original LLaMA and GPT-J across a majority of tasks, and outperforms them in some tasks. We expect that the performance of OpenLLaMA, after completing its training on 1 trillion tokens, will be enhanced even further.
 
 
 | **Task/Metric**        | **GPT-J 6B** | **LLaMA 7B** | **Open LLaMA 7B Preview 200B Tokens** |