Model card updates and fixes

README.md

@@ -1,4 +1,7 @@
 ---
+tags:
+- depth-estimation
+library_name: coreml
 license: apache-2.0
 ---
 
@@ -6,8 +9,6 @@ license: apache-2.0
 
 Depth Anything model was introduced in the paper [Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data](https://arxiv.org/abs/2401.10891) by Lihe Yang et al. and first released in [this repository](https://github.com/LiheYoung/Depth-Anything).
 
-Disclaimer: The team releasing Depth Anything did not write a model card for this model so this model card has been written by the Hugging Face team.
-
 ## Model description
 
 Depth Anything leverages the [DPT](https://huggingface.co/docs/transformers/model_doc/dpt) architecture with a [DINOv2](https://huggingface.co/docs/transformers/model_doc/dinov2) backbone.
@@ -23,12 +24,9 @@ alt="drawing" width="600"/>
 
 | Variant                                                 | Parameters | Size (MB) | Weight precision | Act. precision | abs-rel error | abs-rel reference |
 | ------------------------------------------------------- | ---------: | --------: | ---------------- | -------------- | ------------: | ----------------: |
-| base-original (PyTorch)                                 |      97.5M |       390 | Float32          | Float32        |               |                   |
-| small-original (PyTorch)                                |      24.8M |      99.2 | Float32          | Float32        |        0.1589 |     base-original |
-| [base-float32](depth-anything-base-float32.mlpackage)   |      97.5M |     194.6 | Float32          | Float32        |        0.0056 |     base-original |
-| [base-float16](depth-anything-base-float16.mlpackage)   |      97.5M |     194.6 | Float16          | Float16        |        0.0061 |     base-original |
-| [small-float32](depth-anything-small-float32.mlpackage) |      24.8M |      99.0 | Float32          | Float32        |        0.0073 |    small-original |
-| [small-float16](depth-anything-small-float16.mlpackage) |      24.8M |      45.8 | Float16          | Float16        |        0.0077 |    small-original |
+| [small-original](https://huggingface.co/LiheYoung/depth-anything-small-hf) (PyTorch)                                 |      24.8M |      99.2 | Float32          | Float32        |               |                   |
+| [DepthAnythingSmallF32](DepthAnythingSmallF32.mlpackage) |      24.8M |      99.0 | Float32          | Float32        |        0.0073 |    small-original |
+| [DepthAnythingSmallF16](DepthAnythingSmallF16.mlpackage) |      24.8M |      45.8 | Float16          | Float16        |        0.0077 |    small-original |
 
 ## Evaluation - Inference time
 
@@ -45,10 +43,10 @@ The following results use the small-float16 variant.
 
 ## Download
 
-Install `huggingface-hub`
+Install `huggingface-cli`
 
 ```bash
-pip install huggingface-hub
+brew install huggingface-cli
 ```
 
 To download one of the `.mlpackage` folders to the `models` directory:
@@ -56,8 +54,12 @@ To download one of the `.mlpackage` folders to the `models` directory:
 ```bash
 huggingface-cli download \
   --local-dir models --local-dir-use-symlinks False \
-  coreml-projects/depth-anything \
+  apple/coreml-depth-anything-small \
   --include "DepthAnythingSmallF16.mlpackage/*"
 ```
 
 To download everything, skip the `--include` argument.
+
+## Integrate in Swift apps
+
+The [`huggingface/coreml-examples`](https://github.com/huggingface/coreml-examples/blob/main/depth-anything-example/README.md) repository contains sample Swift code for `coreml-depth-anything-small` and other models. See [the instructions there](https://github.com/huggingface/coreml-examples/tree/main/depth-anything-example) to build the demo app, which shows how to use the model in your own Swift apps.