Mobile Inference and Mobile Models

#ml/mobile

GitHub - open-mmlab/mmdeploy: OpenMMLab Model Deployment Framework d2go/d2go/export at main · facebookresearch/d2go · GitHub

Pytorch

Selective Builds

https://pytorch.org/blog/pytorchs-tracing-based-selective-build/?utm_source=twitter&utm_medium=organic_social&utm_campaign=evergreen

PlayTorch

• playtorch/react-native-pytorch-core at main · facebookresearch/playtorch · GitHub

CoreML

ml-cvnets/README-pytorch-to-coreml.md at main · apple/ml-cvnets · GitHub

OnnxRuntime

• Deploy on mobile | onnxruntime
  • Mobile image recognition on Android | onnxruntime
• GitHub - onnx/onnxmltools: ONNXMLTools enables conversion of models to ONNX
• Model Usability Checker | onnxruntime
• Bringing ONNX models to Android - Surface Duo Blog

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Mobile Models

• GitHub - apple/ml-mobileone: This repository contains the official implementation of the research paper, "An Improved One millisecond Mobile Backbone".
  • GitHub - federicopozzi33/MobileOne-PyTorch: A PyTorch implementation of MobileOne
  • MobileOne — MMClassification 1.0.0rc5 documentation
• MobileVit — MMClassification 1.0.0rc5 documentation
• GitHub - zhangzjn/EMO: Official PyTorch implementation of "Rethinking Mobile Block for Efficient Neural Models"
• GitHub - huawei-noah/Efficient-AI-Backbones: Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
• GitHub - Amshaker/SwiftFormer: SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications
• GitHub - bytedance/Next-ViT