Update README.md

README.md

@@ -25,13 +25,13 @@ From those manipulated distributions, we can study how to effectively detect the
 
 This dataset accompanies the paper:
 
-**Exposing the Illusion of Fairness (EIF): Auditing Vulnerabilities to Distributional Manipulation Attacks**  
+**Exposing the Illusion of Fairness (EIF): Auditing Vulnerabilities to Distributional Manipulation Attacks**  <br/>
 https://arxiv.org/abs/2507.20708  
 
-HF Models repository:
+HF Models repository:<br/>
 https://huggingface.co/ValentinLAFARGUE/EIF-biased-classifiers
 
-Code repository:  
+Code repository:  <br/>
 https://github.com/ValentinLafargue/Inspection  
 
 It contains preprocessed tabular datasets, model outputs, and fairness-related quantities used to analyze bias and mitigation strategies.
@@ -139,7 +139,7 @@ path = hf_hub_download(
 arr = np.load(path)
 ```
 
-For all files:
+For all distribution files (.npy):
 ```
 from huggingface_hub import list_repo_files
 files = list_repo_files("ValentinLAFARGUE/EIF-Manipulated-distributions", repo_type = "dataset")