Update README.md

README.md

@@ -28,7 +28,7 @@ We introduce AceCoder, the first work to propose a fully automated pipeline for
 
 
 ## Note
-- **This model official is trained on the hard version of [TIGER-Lab/AceCode-89K](https://huggingface.co/datasets/TIGER-Lab/AceCode-89K) with about 22k examples, using the binary pass rate (rule based reward) as the reward**
+- **This model is trained on the hard version of [TIGER-Lab/AceCode-89K](https://huggingface.co/datasets/TIGER-Lab/AceCode-89K) with about 22k examples, using the binary pass rate (rule based reward) as the reward**
 <!-- - **This model official is trained on the hard version of [TIGER-Lab/AceCode-89K](https://huggingface.co/datasets/TIGER-Lab/AceCode-89K) with about 22k examples, using the [TIGER-Lab/AceCodeRM-7B](https://huggingface.co/TIGER-Lab/AceCodeRM-7B) as the reward** -->
 - You can reproduce the hard version of [TIGER-Lab/AceCode-89K](https://huggingface.co/datasets/TIGER-Lab/AceCode-89K) using [script in our Github](#)
 - The training takes 6 hours to finish on 8 x H100 GPUs in around 80 optimization steps.