diff --git a/argilla/docs/getting_started/how-to-configure-argilla-on-huggingface.md b/argilla/docs/getting_started/how-to-configure-argilla-on-huggingface.md
index 32b5e4e291..72b5c1ae87 100644
--- a/argilla/docs/getting_started/how-to-configure-argilla-on-huggingface.md
+++ b/argilla/docs/getting_started/how-to-configure-argilla-on-huggingface.md
@@ -107,13 +107,23 @@ HF_TOKEN = "..."
 
 client = rg.Argilla(
     api_url="<api_url>",
-    api_key="<api_key>"
+    api_key="<api_key>",
     headers={"Authorization": f"Bearer {HF_TOKEN}"}
 )
 ```
 
 ## Space Secrets overview
 
-Remember that, by default, Argilla Spaces are configured with a *Sign in with Hugging Face* button, which is also used to grant an `owner` to the creator of the Space. There are two optional secrets to set up the `USERNAME` and `PASSWORD` of the `owner` of Argilla Space. Those are useful when you want to create a different owner user to login into Argilla.
+There's two optional secrets to set up the `USERNAME` and `PASSWORD` of the `owner` of the Argilla Space. Remember that, by default Argilla Spaces are configured with a *Sign in with Hugging Face* button, which is also used to grant an `owner` to the creator of the Space for personal spaces.
 
+The `USERNAME` and `PASSWORD` are only useful in a couple of scenarios:
 
+- You have [disabled Hugging Face OAuth](#how-to-configure-and-disable-oauth-access).
+- You want to [set up Argilla under an organization](#how-to-deploy-argilla-under-a-hugging-face-organization) and want your Hugging Face username to be granted the `owner` role.
+
+In summary, when setting up a Space:
+!!! info "Creating a Space under your personal account"
+    If you are creating the Space under your personal account, **don't insert any value for `USERNAME` and `PASSWORD`**. Once you launch the Space you will be able to Sign in with your Hugging Face username and the `owner` role.
+
+!!! info "Creating a Space under an organization"
+    If you are creating the Space under an organization **make sure to insert your Hugging Face username in the secret `USERNAME`**. In this way, you'll be able to Sign in with your Hugging Face user.
diff --git a/argilla/docs/how_to_guides/dataset.md b/argilla/docs/how_to_guides/dataset.md
index 47ed998fd4..759b4fad74 100644
--- a/argilla/docs/how_to_guides/dataset.md
+++ b/argilla/docs/how_to_guides/dataset.md
@@ -279,7 +279,7 @@ To collect feedback for your dataset, you need to formulate questions that annot
     ```python
     rg.RatingQuestion(
         name="rating",
-        values=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
+        values=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
         title="How satisfied are you with the response?",
         description="1 = very unsatisfied, 10 = very satisfied",
         required=True,
@@ -338,7 +338,7 @@ Metadata properties allow you to configure the use of metadata information for t
     ```python
     rg.TermsMetadataProperty(
         name="terms",
-        options=["group-a", "group-b", "group-c"]
+        options=["group-a", "group-b", "group-c"],
         title="Annotation groups",
         visible_for_annotators=True,
     )
diff --git a/argilla/docs/reference/argilla/records/responses.md b/argilla/docs/reference/argilla/records/responses.md
index f4cb3367ff..6f190b9aa1 100644
--- a/argilla/docs/reference/argilla/records/responses.md
+++ b/argilla/docs/reference/argilla/records/responses.md
@@ -3,7 +3,7 @@ hide: footer
 ---
 # `rg.Response`
 
-Class for interacting with Argilla Responses of records. Responses are answers to questions by a user. Therefore, a recod question can have multiple responses, one for each user that has answered the question. A `Response` is typically created by a user in the UI or consumed from a data source as a label, unlike a `Suggestion` which is typically created by a model prediction.
+Class for interacting with Argilla Responses of records. Responses are answers to questions by a user. Therefore, a question can have multiple responses, one for each user that has answered the question. A `Response` is typically created by a user in the UI or consumed from a data source as a label, unlike a `Suggestion` which is typically created by a model prediction.
 
 ## Usage Examples