Update file README.md

README.md

@@ -126,9 +126,9 @@ The SVM models trained on the quantum-separability dataset. they are grouped by:
 
 The type of the model and the proportion of PPT-ENT states used during training is indicated in the file name. For example the files
 
-SVM_1000_[0.50]_
+SVM_1000_[0.50]_(i)
 
-contain a SVM trained using a dataset of 1000 examples per class where 50% of the entangled examples are PPT-ENT.
+where i is an index between 0 and 4, contain a SVM trained using a dataset of 1000 examples per class where 50% of the entangled examples are PPT-ENT.
 
 All the models are accessible by the function joblib.load in the form of a GridSearchCV model (from sklearn).
 All the models in the library use the Gell-Mann representation of states as input.