diff --git a/docs/40-dev-env/1-dev-setup.mdx b/docs/40-dev-env/1-dev-setup.mdx
index 2095f60..e0ce67c 100644
--- a/docs/40-dev-env/1-dev-setup.mdx
+++ b/docs/40-dev-env/1-dev-setup.mdx
@@ -16,7 +16,7 @@ To do this, choose one of the **Save a copy** options in the **File** menu.
 
 That's it! You're ready for the lab!
 
-## Local setup
+## [Backup] Local setup
 
 :::caution
 Run the notebook locally ONLY IF Google Colab is not an option/doesn't work for you.
diff --git a/docs/50-prepare-the-data/2-chunk-data.mdx b/docs/50-prepare-the-data/2-chunk-data.mdx
index 9d422e5..4ade00b 100644
--- a/docs/50-prepare-the-data/2-chunk-data.mdx
+++ b/docs/50-prepare-the-data/2-chunk-data.mdx
@@ -13,7 +13,7 @@ The answers for code blocks in this section are as follows:
 <div>
 ```python
 RecursiveCharacterTextSplitter.from_tiktoken_encoder(
-    encoding_name="cl100k_base", separators=separators, chunk_size=200, chunk_overlap=30
+    model_name="gpt-4", separators=separators, chunk_size=200, chunk_overlap=30
 )
 ```
 </div>
diff --git a/docs/60-perform-semantic-search/1-concepts.mdx b/docs/60-perform-semantic-search/1-concepts.mdx
index c1a4071..ceb289b 100644
--- a/docs/60-perform-semantic-search/1-concepts.mdx
+++ b/docs/60-perform-semantic-search/1-concepts.mdx
@@ -11,7 +11,7 @@ To perform vector search on your data in MongoDB, you need to create a vector se
       "type": "vector",
       "path": "embedding",
       "numDimensions": 1536,
-      "similarity": "euclidean | cosine | dotProduct"
+      "similarity": "cosine"
     },
     {
       "type": "filter",