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README.md
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@@ -16,17 +16,16 @@ Welcome to the official Hugging Face organization for Apple!
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* Core ML Models
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- [Depth Anything](https://huggingface.co/apple/coreml-depth-anything-small): Depth estimation
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- [DETR Resnet50](https://huggingface.co/apple/coreml-detr-semantic-segmentation): Semantic Segmentation
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- [FastViT](https://huggingface.co/collections/apple/core-ml-fastvit-666b782d98d6421a15237897): Image Classification
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- [Additional Core ML Model Gallery Models](https://huggingface.co/collections/apple/core-ml-gallery-models-666b66ca4e6657b7d179bc42)
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- [Stable Diffusion Core ML models](https://huggingface.co/collections/apple/core-ml-stable-diffusion-666b3b0f4b5f3d33c67c6bbe)
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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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- [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)
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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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* Core ML Models
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- [Depth Anything](https://huggingface.co/apple/coreml-depth-anything-small): Depth estimation
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- [DETR Resnet50](https://huggingface.co/apple/coreml-detr-semantic-segmentation): Semantic Segmentation
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- [FastViT](https://huggingface.co/collections/apple/core-ml-fastvit-666b782d98d6421a15237897): Image Classification
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- [Stable Diffusion Core ML models](https://huggingface.co/collections/apple/core-ml-stable-diffusion-666b3b0f4b5f3d33c67c6bbe)
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- [Additional Core ML Model Gallery Models](https://huggingface.co/collections/apple/core-ml-gallery-models-666b66ca4e6657b7d179bc42)
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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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- [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 in Core ML Tools](https://apple.github.io/coremltools/docs-guides/source/new-features.html)
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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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