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  1. README.md +3 -3
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@@ -65,19 +65,19 @@ Should a specific model be flagged as high risk by our community, we consider:
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  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.
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  <p align="center">
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  <br>
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- <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa1.jpg" alt="screenshot showing where to add tags" />
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  </p>
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  The following tag:
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  <p align="center">
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  <br>
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- <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa_tag.jpg" alt="screenshot showing where to add tags" />
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  </p>
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  Will result in the following warning:
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  <p align="center">
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  <br>
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- <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa2.jpg" alt="screenshot showing where to add tags" />
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  </p>
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  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.
 
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  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.
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  <p align="center">
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  <br>
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+ <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa1.png" alt="screenshot showing where to add tags" />
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  </p>
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  The following tag:
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  <p align="center">
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  <br>
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+ <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" />
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  </p>
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  Will result in the following warning:
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  <p align="center">
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  <br>
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+ <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/ethics_soc_3/nfaa2.png" alt="screenshot showing where to add tags" />
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  </p>
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  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.