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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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- [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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- [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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### 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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### 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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### 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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