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  Welcome to the official Hugging Face organisation for Apple!
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- ## Apple Core ML
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- Build intelligence into your apps using machine learning models from the research community designed for Core ML.
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- ### Image Classification
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- - [FastViT](https://huggingface.co/collections/coreml-projects/coreml-fastvit-666b0053e54816747071d755), a small and very fast model family for image classification.
 
 
 
 
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- <img src="https://huggingface.co/datasets/coreml-projects/documentation-assets/resolve/main/FastViT_2x.png?download=true" width="50%">
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- ### Image Segmentation
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- - [DETR](https://huggingface.co/coreml-projects/coreml-detr-semantic-segmentation). DEtection TRansformer (DETR) allows semantic segmentation on iOS devices, where each pixel in an image is classified according to the most probable category it belongs to.
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- <img src="https://huggingface.co/datasets/coreml-projects/documentation-assets/resolve/main/DETRSegmentation_2x.png?download=true" width="50%">
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-
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- ### Depth Estimation
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- - [Depth Anything](https://huggingface.co/coreml-projects/coreml-depth-anything-small) is a state of the art model for monocular depth estimation.
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- <img src="https://huggingface.co/datasets/coreml-projects/documentation-assets/resolve/main/DepthAnything_2x.png?download=true" width="50%">
 
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- ### Text-to-Image Generation
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- - [Stable Diffusion](https://huggingface.co/collections/apple/core-ml-stable-diffusion-666b3b0f4b5f3d33c67c6bbe) – Core ML versions of Stable Diffusion models for image generation on Apple Silicon.
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- ## Apple Machine Learning Research
 
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- Open research to enable the community to deliver amazing experiences that improve the lives of millions of people every day.
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- - OpenELM [Base](https://huggingface.co/collections/apple/openelm-pretrained-models-6619ac6ca12a10bd0d0df89e) | [Instruct](https://huggingface.co/collections/apple/openelm-instruct-models-6619ad295d7ae9f868b759ca)
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- - [MobileCLIP](https://huggingface.co/collections/apple/mobileclip-models-datacompdr-data-665789776e1aa2b59f35f7c8)
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- - [DataCompDR](https://huggingface.co/collections/apple/mobileclip-models-datacompdr-data-665789776e1aa2b59f35f7c8)
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- - [TiC-CLIP](https://huggingface.co/collections/apple/tic-clip-666097407ed2edff959276e0)
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- - [FLAIR](https://huggingface.co/datasets/apple/flair)
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- ## Other resources
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- - [Hugging Face CoreML Examples](https://github.com/huggingface/coreml-examples) – Run CoreML models like FastViT, DETR and DepthAnything with two lines of code!
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- - [Apple Model Gallery](https://developer.apple.com/machine-learning/models/) – Build intelligence into your apps using machine learning models from the research community designed for Core ML.
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- - [apple/ml-stable-diffusion](https://github.com/apple/ml-stable-diffusion) – Library to run Stable Diffusion on Apple Silicon with Core ML.
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- - [huggingface/swift-coreml-diffusers](https://github.com/huggingface/swift-coreml-diffusers) – Demo app that shows how to integrate `ml-stable-diffusion` in a native Swift application.
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- - [huggingface/swift-transformers](https://github.com/huggingface/swift-transformers) – Swift package to run transformers models on Apple Silicon with Core ML.
 
 
 
 
 
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  Welcome to the official Hugging Face organisation for Apple!
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+ # Apple Core ML – Build intelligence into your apps with Core ML
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+ [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.
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+ ## Core ML Models
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+ - [FastViT](https://huggingface.co/collections/coreml-projects/coreml-fastvit-666b0053e54816747071d755): Image Classification
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+ - [Depth Anything](https://huggingface.co/coreml-projects/coreml-depth-anything-small): Depth estimation.
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+ - [DETR Resnet50](https://huggingface.co/coreml-projects/coreml-detr-semantic-segmentation): Semantic Segmentation
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+ - [Stable Diffusion Core ML models](https://huggingface.co/collections/apple/core-ml-stable-diffusion-666b3b0f4b5f3d33c67c6bbe).
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+ - [Hugging Face Core ML Examples](https://github.com/huggingface/coreml-examples).
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+ # Apple Machine Learning Research
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+ Open research to enable the community to deliver amazing experiences that improve the lives of millions of people every day.
 
 
 
 
 
 
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+ ## Models
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+ - 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)
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+ - [MobileCLIP](https://huggingface.co/collections/apple/mobileclip-models-datacompdr-data-665789776e1aa2b59f35f7c8): Mobile-friendly image-text models.
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+ ## Datasets
 
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+ - [FLAIR](https://huggingface.co/datasets/apple/flair): A large image dataset for federated learning.
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+ - [DataCompDR](https://huggingface.co/collections/apple/mobileclip-models-datacompdr-data-665789776e1aa2b59f35f7c8): Improved datasets for training image-text models.
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+ ## Benchmarks
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+ - [TiC-CLIP](https://huggingface.co/collections/apple/tic-clip-666097407ed2edff959276e0): Benchmark for the design of efficient continual learning of image-text models over years
 
 
 
 
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+ ## Select Highlights and Other Resources
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+ - [Hugging Face CoreML Examples](https://github.com/huggingface/coreml-examples) – Run Core ML models with two lines of code!
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+ - [Apple Model Gallery](https://developer.apple.com/machine-learning/models/)
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+ - [New features](https://apple.github.io/coremltools/docs-guides/source/new-features.html) in Core ML Tools 8
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+ - [Apple Core ML Stable Diffusion](https://github.com/apple/ml-stable-diffusion) – Library to run Stable Diffusion on Apple Silicon with Core ML.
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+ - Hugging Face Blog Posts
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+ - [Releasing Swift Transformers: Run On-Device LLMs in Apple Devices (Aug, 2023)](https://huggingface.co/blog/swift-coreml-llm)
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+ - [Faster Stable Diffusion with Core ML on iPhone, iPad, and Mac](https://huggingface.co/blog/fast-diffusers-coreml)
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+ - [Using Stable Diffusion with Core ML on Apple Silicon](https://huggingface.co/blog/diffusers-coreml)