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Welcome to the official Hugging Face organisation for Apple!
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- [FastViT](https://huggingface.co/collections/coreml-projects/coreml-fastvit-666b0053e54816747071d755)
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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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### Depth Estimation
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- [Stable Diffusion](https://huggingface.co/collections/apple/core-ml-stable-diffusion-666b3b0f4b5f3d33c67c6bbe) β Core ML versions of Stable Diffusion models for image generation on Apple Silicon.
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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
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Welcome to the official Hugging Face organisation for Apple!
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# Apple Core ML β 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) β 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) β 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)
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