diff --git a/notebooks/search/08-learning-to-rank.ipynb b/notebooks/search/08-learning-to-rank.ipynb
index 9b2e95f0..87e0b5ff 100644
--- a/notebooks/search/08-learning-to-rank.ipynb
+++ b/notebooks/search/08-learning-to-rank.ipynb
@@ -8,9 +8,7 @@
    "source": [
     "# How to train and deploy Learning To Rank\n",
     "\n",
-    "TODO: udpate the link to elastic/elasticsearch-labs instead of my fork before merging.\n",
-    "\n",
-    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/elastic/elasticsearch-labs/blob/ltr-notebook/notebooks/search/08-learning-to-rank.ipynb)\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/elastic/elasticsearch-labs/blob/main/notebooks/search/08-learning-to-rank.ipynb)\n",
     "\n",
     "In this notebook we will see an example on how to train a Learning To Rank model using [XGBoost](https://xgboost.ai/) and how to deploy it to be used as a rescorer in Elasticsearch.\n",
     "\n",
@@ -119,7 +117,7 @@
     "\n",
     "In this example notebook we will use a dataset derived from [MSRD](https://github.com/metarank/msrd/tree/master) (Movie Search Ranking Dataset).\n",
     "\n",
-    "The dataset is available [here](https://github.com/elastic/elasticsearch-labs/tree/main/ltr-notebook/notebooks/search/sample_data/learning-to-rank/) and contains the following files:\n",
+    "The dataset is available [here](https://github.com/elastic/elasticsearch-labs/tree/main/notebooks/search/sample_data/learning-to-rank/) and contains the following files:\n",
     "\n",
     "- **movies_corpus.jsonl.gz**: The movies dataset which will be indexed.\n",
     "- **movies_judgements.tsv.gz**: A file containing relevance judgments for a set of queries.\n",
@@ -136,7 +134,7 @@
    "source": [
     "from urllib.parse import urljoin\n",
     "\n",
-    "DATASET_BASE_URL = \"https://raw.githubusercontent.com/elastic/elasticsearch-labs/ltr-notebook/notebooks/search/sample_data/learning-to-rank/\"\n",
+    "DATASET_BASE_URL = \"https://raw.githubusercontent.com/elastic/elasticsearch-labs/main/notebooks/search/sample_data/learning-to-rank/\"\n",
     "\n",
     "CORPUS_URL = urljoin(DATASET_BASE_URL, \"movies-corpus.jsonl.gz\")\n",
     "JUDGEMENTS_FILE_URL = urljoin(DATASET_BASE_URL, \"movies-judgments.tsv.gz\")\n",