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README.md

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 Welcome to the official Hugging Face organisation for Apple!
 
-# Apple Core ML – Build intelligence into your apps with Core ML
+## Apple Core ML – Build intelligence into your apps with Core ML
 
 [Core ML](https://developer.apple.com/machine-learning/core-ml/) is optimized for on-device performance of a broad variety of model types by leveraging Apple Silicon and minimizing memory footprint and power consumption.
 
-## Core ML Models
-
-- [FastViT](https://huggingface.co/collections/coreml-projects/coreml-fastvit-666b0053e54816747071d755): Image Classification
-- [Depth Anything](https://huggingface.co/coreml-projects/coreml-depth-anything-small): Depth estimation
-- [DETR Resnet50](https://huggingface.co/coreml-projects/coreml-detr-semantic-segmentation): Semantic Segmentation
-- [Stable Diffusion Core ML models](https://huggingface.co/collections/apple/core-ml-stable-diffusion-666b3b0f4b5f3d33c67c6bbe)
-- [Hugging Face Core ML Examples](https://github.com/huggingface/coreml-examples)
+* Core ML Models
+  - [FastViT](https://huggingface.co/collections/coreml-projects/coreml-fastvit-666b0053e54816747071d755): Image Classification
+  - [Depth Anything](https://huggingface.co/coreml-projects/coreml-depth-anything-small): Depth estimation
+  - [DETR Resnet50](https://huggingface.co/coreml-projects/coreml-detr-semantic-segmentation): Semantic Segmentation
+  - [Stable Diffusion Core ML models](https://huggingface.co/collections/apple/core-ml-stable-diffusion-666b3b0f4b5f3d33c67c6bbe)
+  - [Hugging Face Core ML Examples](https://github.com/huggingface/coreml-examples)
 
 # Apple Machine Learning Research
 
 Open research to enable the community to deliver amazing experiences that improve the lives of millions of people every day.
 
-## Models
-
-- OpenELM: open, Transformer-based language model. [Base](https://huggingface.co/collections/apple/openelm-pretrained-models-6619ac6ca12a10bd0d0df89e) | [Instruct](https://huggingface.co/collections/apple/openelm-instruct-models-6619ad295d7ae9f868b759ca)
-- [MobileCLIP](https://huggingface.co/collections/apple/mobileclip-models-datacompdr-data-665789776e1aa2b59f35f7c8): Mobile-friendly image-text models.
-
-## Datasets
-
-- [FLAIR](https://huggingface.co/datasets/apple/flair): A large image dataset for federated learning.
-- [DataCompDR](https://huggingface.co/collections/apple/mobileclip-models-datacompdr-data-665789776e1aa2b59f35f7c8): Improved datasets for training image-text models.
-
-## Benchmarks
-
-- [TiC-CLIP](https://huggingface.co/collections/apple/tic-clip-666097407ed2edff959276e0): Benchmark for the design of efficient continual learning of image-text models over years
+* Models
+  - OpenELM: open, Transformer-based language model. [Base](https://huggingface.co/collections/apple/openelm-pretrained-models-6619ac6ca12a10bd0d0df89e) | [Instruct](https://huggingface.co/collections/apple/openelm-instruct-models-6619ad295d7ae9f868b759ca)
+  - [MobileCLIP](https://huggingface.co/collections/apple/mobileclip-models-datacompdr-data-665789776e1aa2b59f35f7c8): Mobile-friendly image-text models.
+* Datasets
+  - [FLAIR](https://huggingface.co/datasets/apple/flair): A large image dataset for federated learning.
+  - [DataCompDR](https://huggingface.co/collections/apple/mobileclip-models-datacompdr-data-665789776e1aa2b59f35f7c8): Improved datasets for training image-text models.
+* Benchmarks
+  - [TiC-CLIP](https://huggingface.co/collections/apple/tic-clip-666097407ed2edff959276e0): Benchmark for the design of efficient continual learning of image-text models over years
  
 # Select Highlights and Other Resources