Update README.md

README.md

@@ -494,6 +494,10 @@ Stack-Edu is a 125B token dataset of educational code filtered from [The Stack v
 
 This dataset was curated using a classifier-based filtering strategy, inspired by [📚 FineWeb-Edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu), to retain only the highest-quality educational programming content.
 
+Stack-Edu shows consistent improvement over StarCoder2data on all the programming languages on MultiPL-E benchmark.
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/GWnPgD0diMu0I8buK6mvG.png" width="600"/>
+
 ## Downloading the data
 This dataset only contains the SWHIDs to download the code files and not the content of the files itself. The contents can be downloaded from Software Heritage's S3 bucket to ensure data compliance. 
 Please refer to [the-stack-v2](https://huggingface.co/datasets/bigcode/the-stack-v2-train-full-ids) for the data license.
@@ -556,17 +560,13 @@ The table below shows the number of tokens in each programming language using [S
 | Ruby       | 1.61                 |
 
 
-## Dataset curation and results
+## Dataset curation
 To build Stack-Edu, we:
 
 - Selected 15 largest programming languages from StarCoder2Data 
 - Trained 15 language-specific classifiers, using [StarEncoder](https://huggingface.co/bigcode/starencoder) model on synthetic annotations generated by Llama3-70B-Instruct. The classifiers for each language are available in this [collection](https://huggingface.co/collections/HuggingFaceTB/the-ultimate-collection-of-code-classifiers-67b5aa3eb8994a4b71453005).
 - Applied a filtering threshold of 3 (out of 5) to retain highly educational content, except for Java, which performed best at threshold 2.
 
-Stack-Edu shows consistent improvement over StarCoder2data on all the programming languages on MultiPL-E benchmark.
-
-<img src="https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/GWnPgD0diMu0I8buK6mvG.png" width="600"/>
-
 ## Citation Information
 
 ```