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EdgeInfer enables efficient edge intelligence by running small AI models, including embeddings and OnnxModels, on resource-constrained devices like Android, iOS, or MCUs for real-time decision-making. EdgeInfer 旨在资源受限的设备上运行小型 AI 模型(包括向量化和 Onnx 模型),如 Android、iOS 或 MCUs,实现高效的边缘智能,用于实时决策。

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unit-mesh/edge-infer

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Edge Infer

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EdgeInfer enables efficient edge intelligence by running small AI models, including embeddings and OnnxModels, on resource-constrained devices like Android, iOS, or MCUs for real-time decision-making.

Architecture:

EdgeMind Architecture

Platform support (by Design):

  • Android, iOS
  • Linux, Windows, Mac,
  • Raspberry Pi, MCU

Todos

  • Inference wrapper
    • Onnx Runtime
    • Tokenizer
  • UniFFI, is a toolkit for building cross-platform software components in Rust.
  • GRPC server with tonic
  • Multiple OS support:
    • Desktop: Windows, Mac, Linux (x86, x64)
    • Mobile: Android, iOS, Linux (ARM)
    • Embedded Linux (ARM).
  • Flexible Configuration: Easily configurable via command-line parameters, including listening port, batch size, thread count, and others.

Usecases

Resources

Examples:

  • Modern cross-platform telemetry: Glean

MCU

ToSpike

Not working:

License

This project is licensed under the MIT License, See LICENSE for the full license text.

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EdgeInfer enables efficient edge intelligence by running small AI models, including embeddings and OnnxModels, on resource-constrained devices like Android, iOS, or MCUs for real-time decision-making. EdgeInfer 旨在资源受限的设备上运行小型 AI 模型(包括向量化和 Onnx 模型),如 Android、iOS 或 MCUs,实现高效的边缘智能,用于实时决策。

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