Create README.md

README.md

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+---
+license: apache-2.0
+pipeline_tag: mask-generation
+library_name: coreml
+---
+
+# SAM2 Small Core ML
+
+SAM 2 (Segment Anything in Images and Videos), is a collection of foundation models from FAIR that aim to solve promptable visual segmentation in images and videos. See the [SAM 2 paper](https://arxiv.org/abs/2408.00714) for more information.
+
+This is the Core ML version of [SAM 2 Tiny](https://huggingface.co/facebook/sam2-hiera-tiny), and is suitable for use with the [SAM2 Studio demo app](https://github.com/huggingface/sam2-studio). It was converted in `float16` precision using [this fork](https://github.com/huggingface/segment-anything-2/tree/coreml-conversion) of the original code repository.
+
+## Download
+
+Install `huggingface-cli`
+
+```bash
+brew install huggingface-cli
+```
+
+```bash
+huggingface-cli download --local-dir models coreml-projects/coreml-sam2-small
+```
+
+## Citation
+
+To cite the paper, model, or software, please use the below:
+```
+@article{ravi2024sam2,
+  title={SAM 2: Segment Anything in Images and Videos},
+  author={Ravi, Nikhila and Gabeur, Valentin and Hu, Yuan-Ting and Hu, Ronghang and Ryali, Chaitanya and Ma, Tengyu and Khedr, Haitham and R{\"a}dle, Roman and Rolland, Chloe and Gustafson, Laura and Mintun, Eric and Pan, Junting and Alwala, Kalyan Vasudev and Carion, Nicolas and Wu, Chao-Yuan and Girshick, Ross and Doll{\'a}r, Piotr and Feichtenhofer, Christoph},
+  journal={arXiv preprint arXiv:2408.00714},
+  url={https://arxiv.org/abs/2408.00714},
+  year={2024}
+}
+```