diff --git a/examples/training/distillation/model_distillation.py b/examples/training/distillation/model_distillation.py
index b3b6f69dd..9f89af3d2 100644
--- a/examples/training/distillation/model_distillation.py
+++ b/examples/training/distillation/model_distillation.py
@@ -56,16 +56,6 @@
 inference_batch_size = 64
 train_batch_size = 64
 
-# We use AllNLI as a source of sentences for the distillation
-nli_dataset_path = "datasets/AllNLI.tsv.gz"
-
-# Further, we use sentences extracted from the English Wikipedia to train the distillation
-wikipedia_dataset_path = "datasets/wikipedia-en-sentences.txt.gz"
-
-# We use the STS benchmark dataset to see how much performance we loose
-sts_dataset_path = "datasets/stsbenchmark.tsv.gz"
-
-
 logging.info("Load the AllNLI dataset")
 # Load the AllNLI dataset: https://huggingface.co/datasets/sentence-transformers/all-nli
 nli_train_dataset = load_dataset("sentence-transformers/all-nli", "pair-score", split="train")