Update README.md

README.md

@@ -53,7 +53,7 @@ filtered_ds = ds.filter(lambda x: x['score'] > 3)
 
 ## Dataset creation
 
-In a nutshell, we use Llama-3.1-70B to grade the educational quality of 550k samples from the original dataset. Then, we used these samples to train a encoder-based classifier, so that it learns to assign a score from 0 to 5. Since this model is cheaper to use than an GPT, we can run it at scale over the entire dataset, thus allowing us to filter a high-quality section from it.
+In a nutshell, we use Llama-3.1-70B to grade the educational quality of 550k samples from the original dataset. Then, we used these samples to train a encoder-based classifier, so that it learns to assign a score from 0 to 5. Since this model is cheaper to use than a GPT, we can run it at scale over the entire dataset, thus allowing us to filter a high-quality section from it.
 
 Here is an overview of the architecture: