Update README.md

README.md

@@ -62,24 +62,28 @@ Should a specific model be flagged as high risk by our community, we consider:
 
 **How to add the “Not For All Audiences” tag:**
 
-Edit the model/data card → add `not-for-all-audiences` in the tags section → open the PR and wait for the authors to merge it.
+Edit the model/data card → add `not-for-all-audiences` in the tags section → open the PR and wait for the authors to merge it. Once merged, the following tag will be displayed on the repository:
+
 <p align="center">
  <br>
- <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa1.png" alt="screenshot showing where to add tags" />
+ <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa_tag.png" alt="screenshot showing where to add tags" />
 </p>
 
-The following tag:
+Any repository tagged `not-for-all-audiences` will display the following popup when visited:
+
 <p align="center">
  <br>
- <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa_tag.png" alt="screenshot showing where to add tags" />
+ <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa2.png" alt="screenshot showing where to add tags" />
 </p>
 
-Will result in the following warning:
+Clicking "View Content" will allow you to view the repository as normal. If you wish to always view `not-for-all-audiences`-tagged repositories without the popup, this setting can be changed in a user's [Content Preferences](https://huggingface.co/settings/content-preferences)
+
 <p align="center">
  <br>
- <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa2.png" alt="screenshot showing where to add tags" />
+ <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa1.png" alt="screenshot showing where to add tags" />
 </p>
 
+
 Open science requires safeguards, and one of our goals is to create an environment informed by tradeoffs with different values. Hosting and providing access to models in addition to cultivating community and discussion empowers diverse groups to assess social implications and guide what is good machine learning.