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docs/source/en/model_doc/depth_anything.md

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-# Depth Anything
+# Depth Anything and Depth Anything V2
 
 ## Overview
 
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 <small> Depth Anything overview. Taken from the <a href="https://arxiv.org/abs/2401.10891">original paper</a>.</small>
 
-This model was contributed by [nielsr](https://huggingface.co/nielsr).
-The original code can be found [here](https://github.com/LiheYoung/Depth-Anything).
+Depth Anything V2 was introduced in [the paper of the same name](https://arxiv.org/abs/2406.09414) by Lihe Yang et al. It uses the same architecture as the original Depth Anything release, but uses synthetic data and a larger capacity teacher model to achieve much finer and robust depth predictions.
+
+This models were contributed by [nielsr](https://huggingface.co/nielsr).
+The original code can be found [here (V1)](https://github.com/LiheYoung/Depth-Anything) and [here (V2)](https://github.com/DepthAnything/Depth-Anything-V2).
 
 ## Usage example
 
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 - [Monocular depth estimation task guide](../tasks/depth_estimation)
 - A notebook showcasing inference with [`DepthAnythingForDepthEstimation`] can be found [here](https://github.com/NielsRogge/Transformers-Tutorials/blob/master/Depth%20Anything/Predicting_depth_in_an_image_with_Depth_Anything.ipynb). 🌎
+- [Depth Anything V2 demo](https://huggingface.co/spaces/depth-anything/Depth-Anything-V2).
+- [Core ML conversion of the `small` variant for use on Apple Silicon](https://huggingface.co/apple/coreml-depth-anything-v2-small).
 
 If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we'll review it! The resource should ideally demonstrate something new instead of duplicating an existing resource.