Model card updates and fixes

README.md

@@ -1,15 +1,16 @@
 ---
+tags:
+- image-segmentation
+library_name: coreml
 license: apache-2.0
 ---
 
 # DETR-Resnet50 (semantic segmentation) Core ML Models
 
-See [the Files tab](https://huggingface.co/coreml-projects/detr-resnet50-semantic-segmentation/tree/main) for converted models.
+See [the Files tab](tree/main) for converted models.
 
 DEtection TRansformer (DETR) model trained end-to-end on COCO 2017 object detection (118k annotated images). It was introduced in the paper [End-to-End Object Detection with Transformers](https://arxiv.org/abs/2005.12872) by Carion et al. and first released in [this repository](https://github.com/facebookresearch/detr). 
 
-Disclaimer: The team releasing DETR did not write a model card for this model so this model card has been written by the Hugging Face team.
-
 ## Model description
 
 The DETR model is an encoder-decoder transformer with a convolutional backbone. Two heads are added on top of the decoder outputs in order to perform object detection: a linear layer for the class labels and a MLP (multi-layer perceptron) for the bounding boxes. The model uses so-called object queries to detect objects in an image. Each object query looks for a particular object in the image. For COCO, the number of object queries is set to 100. 
@@ -42,10 +43,10 @@ The following results refer to DETRResnet50SemanticSegmentationF16. The compute
 
 ## 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:
@@ -53,8 +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/detr-resnet50-semantic-segmentation \
-  --include "detr-resnet50-semantic-400-float16.mlpackage/*"
+  apple/coreml-detr-semantic-segmentation \
+  --include "DETRResnet50SemanticSegmentationF16.mlpackage/*"
 ```
 
-To download everything, skip the `--include` argument.
+To download everything, skip the `--include` argument. This will retrieve `float32` and `float16` variants, as well as quantized versions of the `float16` variant.
+
+## 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-detr-semantic-segmentation` and other models. See [the instructions there](https://github.com/huggingface/coreml-examples/blob/main/SemanticSegmentationSample/README.md) to build the demo app, which shows how to use the model in your own Swift apps.